references.bib

%% Created using Papers on Mon, 13 Jun 2016.
%% http://papersapp.com/papers/

@article{Boykov:2001de,
author = {Boykov, Y and Veksler, O and Zabih, R},
title = {{Fast approximate energy minimization via graph cuts}},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
year = {2001},
volume = {23},
number = {11},
pages = {1222--1239}
}

@inproceedings{Borst:2003ch,
author = {Borst, C and Fischer, M and Hirzinger, G},
title = {{Grasping the dice by dicing the grasp}},
booktitle = {2003 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2003},
pages = {3692--3697}
}

@article{Thrun:1998ex,
author = {Thrun, Sebastian and Burgard, Wolfram and Fox, Dieter},
title = {{A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots}},
journal = {Autonomous Robots},
year = {1998},
volume = {5},
number = {3/4},
pages = {253--271}
}

@inproceedings{Jaakkola00tutorialon,
author = {Jaakkola, Tommi S},
title = {{Tutorial on Variational Approximation Methods}},
booktitle = {In Advanced Mean Field Methods: Theory and Practice},
year = {2000},
pages = {129--159},
publisher = {MIT Press}
}

@article{Pan:2010wx,
author = {Pan, S J and Yang, Q},
title = {{A Survey on Transfer Learning}},
journal = {{\ldots} and Data Engineering},
year = {2010}
}

@article{Tzikas:2008fu,
author = {Tzikas, D G and Likas, A C and Galatsanos, N P},
title = {{The variational approximation for Bayesian inference}},
journal = {Signal Processing Magazine, IEEE},
year = {2008},
volume = {25},
number = {6},
pages = {131--146}
}

@article{Rosales:2010gl,
author = {Rosales, C and Ros, L and Porta, J M and Suarez, R},
title = {{Synthesizing Grasp Configurations with Specified Contact Regions}},
journal = {The International Journal of Robotics Research},
year = {2010},
month = jul
}

@inproceedings{madry2012ICRA_SPME,
author = {Madry, Marianna and Song, Dan and Ek, Carl Henrik and Kragic, Danica},
title = {{''Robot bring me something to drink from": object representation for transferring task specific grasps}},
booktitle = {The ICRA'12 Workshop on Semantic Perception, Mapping and Exploration (SPME)},
year = {2012}
}

@article{Yuruten:2013hr,
author = {Yuruten, O and Sahin, E and Kalkan, S},
title = {{The learning of adjectives and nouns from affordance and appearance features}},
journal = {Adaptive Behavior},
year = {2013},
volume = {21},
number = {6},
pages = {437--451},
month = nov
}

@inproceedings{detry2013ICRA,
author = {Detry, Renaud and Ek, Carl Henrik and Madry, Marianna and Kragic, Danica},
title = {{Compressing Grasping Experience into a Dictionary of Prototypical Grasp-predicting Parts}},
booktitle = {The 5th International Workshop on Human-Friendly Robotics},
year = {2012},
month = oct
}

@article{Oztop:2004ed,
author = {Oztop, Erhan and Bradley, NinaS and Arbib, MichaelA},
title = {{Infant grasp learning: a computational model}},
journal = {Experimental Brain Research},
year = {2004},
volume = {158},
number = {4},
pages = {480--503},
month = jun
}

@inproceedings{madry2012ICRA,
author = {Madry, Marianna and Song, Dan and Kragic, Danica},
title = {{D/3D Object Categorization for Task Based Grasping}},
booktitle = {European Robotics Forum 2011: RGB-D Workshop on 3D Perception in Robotics},
year = {2011},
month = apr,
annote = {extended abstract}
}

@article{Rosch:1976cc,
author = {Rosch, Eleanor and Mervis, Carolyn B and Gray, Wayne D and Johnson, David M and Boyes-Braem, Penny},
title = {{Basic objects in natural categories}},
journal = {Cognitive psychology},
year = {1976},
volume = {8},
number = {3},
pages = {382--439},
month = jul
}

@article{Qian:2012ta,
author = {Qian, X and Tang, Y Yan and Yan, Z and Hang, Kaiyu},
title = {{ISABoost: A weak classifier inner structure adjusting based AdaBoost algorithm---ISABoost based application in scene categorization}},
journal = {Neurocomputing},
year = {2012}
}

@inproceedings{Song:2011cy,
author = {Song, Dan and Ek, Carl Henrik and Huebner, Kai and Kragic, Danica},
title = {{Multivariate discretization for Bayesian Network structure learning in robot grasping}},
booktitle = {2011 IEEE International Conference on Robotics and Automation},
year = {2011},
pages = {1944--1950}
}

@article{Argall:2009hh,
author = {Argall, Brenna D and Chernova, Sonia and Veloso, Manuela and Browning, Brett},
title = {{A survey of robot learning from demonstration}},
journal = {Robotics and Autonomous Systems},
year = {2009},
volume = {57},
number = {5},
pages = {469--483},
month = may
}

@article{Ruhnke:2013tt,
author = {Ruhnke, M and Bo, L and Fox, Dieter and Burgard, Wolfram},
title = {{Compact RGBD Surface Models Based on Sparse Coding}},
year = {2013}
}

@inproceedings{Detry:vc,
author = {Detry, Renaud and Hjelm, Martin and Ek, Carl Henrik and Kragic, Danica},
title = {{Generalizing Task Parameters Through Modularization}},
booktitle = {ICRA Workshop on Autonomous Learning}
}

@article{Borst:2004wf,
author = {Borst, C and Fischer, M and Hirzinger, G},
title = {{Grasp Planning: How to Choose a Suitable Task Wrench Space}},
journal = {Robotics {\&} Automation {\ldots}},
year = {2004}
}

@article{Wang:2012uo,
author = {Wang, Chong and Blei, David M.},
title = {{Variational Inference in Nonconjugate Models}},
journal = {arXiv.org},
year = {2012},
eprint = {1209.4360v4},
eprinttype = {arxiv},
eprintclass = {stat.ML},
month = sep
}

@inproceedings{detry2010c,
author = {Detry, Renaud and Piater, Justus},
title = {{Continuous Surface-point Distributions for 3D Object Pose Estimation and Recognition}},
booktitle = {Asian Conference on Computer Vision},
year = {2010},
pages = {572--585},
annote = {
Basic idea: model the object in 3D by computing a probability distribution acrross it surface. The proability distributions is calculated by using KDE on samples from the object. 

}
}

@inproceedings{Griffith:2009cm,
author = {Griffith, S and Sinapov, J and Miller, M and Stoytchev, A},
title = {{Toward interactive learning of object categories by a robot: A case study with container and non-container objects}},
booktitle = {Development and Learning, 2009. ICDL 2009. IEEE 8th International Conference on},
year = {2009},
pages = {1--6},
annote = {<b>Summary:</b>

Problem: To learn a robot from sensory-motor experince what is a container and not a container. And to use the sensory-motor experience to classfiy novel objects to a specific category.

The robot drops a cube into a container that is either up or up-side down and oberseves the outcome. It then tries to push the container and depedning on the co-movement or no co-movement with the cube it can learn a functional representation of the object.

In some sense this is clustering based upon outcome experience rather than then clustering of features; so there is a temporal aspect to it that is interesting.

The not so cool part is that the clustering into the two groups container and not a container is not so convincing, and that the classificiation that they do on novel objects based upon the image features they extracted are kind of riddiciolous. 






}
}

@inproceedings{Tsai:2011kd,
author = {Tsai, G and Xu, Changhai and Liu, Jingen and Kuipers, Benjamin J},
title = {{Real-time indoor scene understanding using Bayesian filtering with motion cues}},
booktitle = {Computer Vision (ICCV), 2011 IEEE International Conference on},
year = {2011},
pages = {121--128}
}

@article{Bo:2011ve,
author = {Bo, L and Ren, X and Fox, Dieter},
title = {{Hierarchical matching pursuit for image classification: Architecture and fast algorithms}},
journal = {Advances in Neural Information {\ldots}},
year = {2011}
}

@inproceedings{Singhi:2006jz,
author = {Singhi, Surendra K and Liu, Huan},
title = {{Feature subset selection bias for classification learning}},
booktitle = {ICML '06: Proceedings of the 23rd international conference on Machine learning},
year = {2006},
publisher = { ACM},
month = jun
}

@article{McCarty:2001dr,
author = {McCarty, Michael E and Clifton, Rachel K and Ashmead, Daniel H and Lee, Philip and Goubet, Nathalie},
title = {{How Infants Use Vision for Grasping Objects}},
journal = {Child Development},
year = {2001},
volume = {72},
number = {4},
pages = {973--987},
month = aug
}

@inproceedings{Thrun:2000il,
author = {Thrun, Sebastian and Burgard, Wolfram and Fox, Dieter},
title = {{A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping}},
booktitle = {2000 IEEE International Conference on Robotics and Automation},
year = {2000},
pages = {321--328}
}

@article{Afkham:2008ez,
author = {Afkham, H M and Targhi, A T and Eklundh, J-O and Pronobis, A},
title = {{Joint visual vocabulary for animal classification}},
journal = {International Conference on Pattern Recognition. Proceedings},
year = {2008},
pages = {1--4},
month = dec
}

@inproceedings{Gienger:2008gk,
author = {Gienger, M and Toussaint, M and Goerick, C},
title = {{Task maps in humanoid robot manipulation}},
booktitle = {2008 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2008},
pages = {2758--2764}
}

@article{Widynski:2014dc,
author = {Widynski, Nicolas and Moevus, Antoine and Mignotte, Max},
title = {{Local symmetry detection in natural images using a particle filtering approach.}},
journal = {IEEE transactions on image processing : a publication of the IEEE Signal Processing Society},
year = {2014},
volume = {23},
number = {12},
pages = {5309--5322},
month = dec
}

@book{Hastie:2009wp,
author = {Hastie, Trevor and Tibshirani, Robert and Friedman, Jerome},
title = {{The Elements of Statistical Learning}},
publisher = {Springer},
year = {2009},
series = {Data Mining, Inference, and Prediction, Second Edition},
month = aug,
annote = {Consider minimizing D∗ subject to ||$\beta$|| = 1. Describe this criterion in words. Does it solve the optimal separating hyperplane problem?
}
}

@article{Billard:2006vb,
author = {Billard, A G and Calinon, S and Guenter, F},
title = {{Discriminative and adaptive imitation in uni-manual and bi-manual tasks}},
journal = {Robotics and Autonomous Systems},
year = {2006}
}

@inproceedings{Geiger:2009bc,
author = {Geiger, Andreas and Urtasun, Raquel and Darrell, Trevor J},
title = {{Rank priors for continuous non-linear dimensionality reduction}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2009 IEEE Conference on},
year = {2009},
pages = {880--887}
}

@book{Heckerman:2008fh,
author = {Heckerman, David},
editor = {Holmes, Dawn E and Jain, Lakhmi C},
title = {{Studies in Computational Intelligence}},
publisher = {Springer Berlin Heidelberg},
year = {2008},
volume = {156},
series = {Studies in Computational Intelligence},
address = {Berlin, Heidelberg}
}

@article{Gelman:2002wx,
author = {Gelman, Andrew},
title = {{Prior Distribution}},
journal = {Encyclopedia of Environmetrics},
year = {2002},
volume = {3},
pages = {1634--1637},
month = apr
}

@inproceedings{Geiger:2011il,
author = {Geiger, Andreas and Lauer, M and Urtasun, Raquel},
title = {{A generative model for 3D urban scene understanding from movable platforms}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on},
year = {2011},
pages = {1945--1952}
}

@article{Gelman:1996ul,
author = {Gelman, Andrew},
title = {{Bayesian Model-Building By Pure Thought: Some Principles And Examples}},
journal = {Statistica Sinica},
year = {1996},
volume = {6},
pages = {215--232},
month = apr
}

@article{AlexJSmola:2001vr,
author = {Smola, Alexander J and Bartlett, Peter},
title = {{Sparse Greedy Gaussian Process Regression}},
year = {2001}
}

@inproceedings{Delong:2010bk,
author = {Delong, A and Osokin, A and Isack, H N and Boykov, Y},
title = {{Fast approximate energy minimization with label costs}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on},
year = {2010},
pages = {2173--2180}
}

@article{Sutton:2010we,
author = {Sutton, Charles and McCallum, Andrew},
title = {{An Introduction to Conditional Random Fields}},
journal = {arXiv.org},
year = {2010},
eprint = {1011.4088v1},
eprinttype = {arxiv},
eprintclass = {stat.ML},
month = nov
}

@inproceedings{Li:1987gj,
author = {Li, Zexiang and Sastry, S},
title = {{Task oriented optimal grasping by multifingered robot hands}},
booktitle = {1987 IEEE International Conference on Robotics and Automation},
year = {1987},
pages = {389--394}
}

@article{Zhou:2011ts,
author = {Zhou, Yang},
title = {{Structure Learning of Probabilistic Graphical Models: A Comprehensive Survey}},
journal = {arXiv.org},
year = {2011},
eprint = {1111.6925v1},
eprinttype = {arxiv},
eprintclass = {stat.ML},
month = nov,
annote = {survey on structure learning}
}

@inproceedings{Stober:2011iv,
author = {Stober, Jeremy and Miikkulainen, Risto and Kuipers, Benjamin J},
title = {{Learning geometry from sensorimotor experience}},
booktitle = {2011 IEEE International Conference on Development and Learning},
year = {2011},
pages = {1--6},
publisher = {IEEE}
}

@article{Sharan:2013cn,
author = {Sharan, Lavanya and Liu, Ce and Rosenholtz, Ruth and Adelson, Edward H},
title = {{Recognizing Materials Using Perceptually Inspired Features}},
journal = {International Journal of Computer Vision},
year = {2013},
volume = {103},
number = {3},
pages = {348--371},
month = feb
}

@article{Argyros:2006in,
author = {Argyros, Antonis A and Lourakis, Manolis I A},
title = {{Vision-Based Interpretation of Hand Gestures for Remote Control of a Computer Mouse}},
journal = {Computer Vision in Human-Computer Interaction},
year = {2006},
volume = {3979},
number = {Chapter 5},
pages = {40--51},
annote = {Thoughts: Where is the line between hardware accelerated research and common simple hardware using algorithmic focused acceleration?

Review: 

This paper developes a method for gesture interaction with a mouse / point{\&}amp;click GUI. They hardware used is a simple common webcam on a ordinary computer thus no extra or advanced hardware is used i.e. things lie in the algorithm rather than in the hardware. There are two systems one in 2D and one 3D. Pretty boring.
 }
}

@article{Zhang:2004ft,
author = {Zhang, Jianwei and R{\"o}ssler, Bernd},
title = {{Self-valuing learning and generalization with application in visually guided grasping of complex objects}},
journal = {Robotics and Autonomous Systems},
year = {2004},
volume = {47},
number = {2-3},
pages = {117--127},
month = jun
}

@article{Getoor:2007vs,
author = {Getoor, L and Taskar, B},
title = {{Introduction to Statistical Relational Learning - Lise Getoor - Google Books}},
year = {2007}
}

@article{Rothrock:vt,
author = {Rothrock, B and Park, S and Zhu, S C},
title = {{Integrating Grammar and Segmentation for Human Pose Estimation}},
journal = {cs.ucla.edu
}
}

@inproceedings{Wohlkinger:2011da,
author = {Wohlkinger, W and Vincze, M},
title = {{Ensemble of shape functions for 3D object classification}},
booktitle = {Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on},
year = {2011},
pages = {2987--2992}
}

@inproceedings{Bitzer:2009hn,
author = {Bitzer, Sebastian and Vijayakumar, Sethu},
title = {{Latent Spaces for Dynamic Movement Primitives}},
booktitle = {2009 IEEE-RAS International Conference on Humanoid Robots (Humanoids)},
year = {2009},
pages = {574--581},
publisher = {IEEE}
}

@article{Balasubramanian:2012hb,
author = {Balasubramanian, R and Xu, Ling and Brook, P D and Smith, J R and Matsuoka, Y},
title = {{Physical Human Interactive Guidance: Identifying Grasping Principles From Human-Planned Grasps}},
journal = {Robotics, IEEE Transactions on},
year = {2012},
volume = {28},
number = {4},
pages = {899--910}
}

@inproceedings{Thrun:1999eu,
author = {Thrun, Sebastian and Bennewitz, M and Burgard, Wolfram and Cremers, A B and Dellaert, F and Fox, Dieter and Hahnel, D and Rosenberg, C and Roy, N and Schulte, J and Schulz, D},
title = {{MINERVA: a second-generation museum tour-guide robot}},
booktitle = {1999 IEEE International Conference on Robotics and Automation},
year = {1999},
pages = {1999--2005}
}

@article{Zhou:2014ta,
author = {Zhou, Bolei and Khosla, Aditya and Lapedriza, Agata and Oliva, Aude and Torralba, Antonio},
title = {{Object Detectors Emerge in Deep Scene CNNs}},
journal = {arXiv.org},
year = {2014},
month = dec
}

@article{Neal:2003tm,
author = {Neal, R M},
title = {{Density modeling and clustering using Dirichlet diffusion trees}},
journal = {Bayesian Statistics},
year = {2003}
}

@article{Schenck:2013ts,
author = {Schenck, C and Sinapov, J and Staley, K},
title = {{Grounded Object Individuation
by a Humanoid Robot}},
journal = {engineering.iastate.edu
},
year = {2013},
month = nov
}

@article{James:1997uh,
author = {James, G and Hastie, T},
title = {{Generalizations of the Bias Variance Decomposition for Prediction Error}},
journal = {Dept Statistics},
year = {1997}
}

@article{Kiros:2014wb,
author = {Kiros, Ryan and Salakhutdinov, Ruslan and Zemel, Richard S},
title = {{Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models}},
journal = {arXiv.org},
year = {2014},
eprint = {1411.2539v1},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = nov,
annote = {13 pages. NIPS 2014 deep learning workshop}
}

@article{Zabulis:2009tz,
author = {Zabulis, X and Baltzakis, HG and Argyros, Antonis A},
title = {{Vision-based hand gesture recognition for human-computer interaction}},
journal = {The Universal Access Handbook},
year = {2009},
annote = {<b>Some thoughts</b>
Detection is separate from learning and understanding gestures etc. Since all we have to know is how a hand looks like in order to detect it. 

Learning and understanding must be put in the context of previously aquired knowledge or combinations of such. 

Gestures understanding should be correlated with facial expressions and body poses. Body language. Seems that no one has added this approach from what I have read so far. Imagine having an paralell HMM for facial expressions and pose. Also how about the Tobii eye detecion this is also very related to some gestures like pointing at objects, thinking and showing emotions.   

<b>Review</b>
An overview of hand/gesture recognition. The authors identify three building blocks of hand gesture inference: detection, tracking and recognition.

<b>Detection</b> consists of the detection of hands and the segementation of the image  to understand the context and remove irrelevant data. There are several features that are used in the detection stage. 

- <b>Skin color</b>; which is problematic since there is a lot of variance of the skin color in human beings and there is also lot of different lightning conditions adding up to the ambiguity.

- <b>Shape</b>: Edge detection to find the hands. Often combined with color since there is a lot of ambiguity and occlusion. To deal with the clutter some people have used particle filters. There has also been some research into morphology however it seems kind of rudimentary. I am sure something could be done to enhance the morphology approach.

- <b>Pixel values</b>: the ordinary template matching and boosting approach.

- <b>Motion</b>: seems like this feature is a bit unused except for the motion residue idea that hands move more than other objects in the scene. I guess if one wants to detect the hands one starts at frame 1 and then move on to the next frame. So real time seems a bit difficult maybe more applicable when analyzing a sequence.

<b>Tracking</b>
The tracking part deals with keeping track of where the hands go. Basically so that one does not have to do the detection over  again. 

- <b>Templates</b>: basically once the hands have been detected that part is used as template for detecting the hand in the next frame. There are also contour blob templates that are deformed to fit the hand contour in the next frame. Good approach but very sensitive to clutter. 

- <b>Optimal estimation techniques</b>: Kalman filtering framework. Hard to understand since I have forgotten what Kalman filtering is...

- <b>Mean shift algorithm</b>: should investigate how it works.

- <b>Particle filtering</b> {\&}amp; condensation algorithm to be investigated.

<b>Recognition</b>
Interpreting the semantics that the hand(s) location, posture, or gesture conveys. The paper defines two categories: 1) interpretation of control applications such as drawing lines etc. A bit unclear definition actually. What this should mean is actually action understanding. Right? Or would this get filed under 2 as well. Very ambigious and unclear.  2) Interpretatioon of gestures, postures, signs etc. Then they talk about how this phase is context driven and how HMMs are a good framework for the understanding. Some approaches are outlined below.

- <b>Template matching</b>: Same procedure as with facerecognition. The only difference here is that here we are essentially dealing with a 360 degree object but for faces there is only about 180 which certainly makes recognition a bit harder. A lot of people seems to be doing multiple views templates plus a coordination with previous frames matched templates. There is also some kind histogram idea which doesn't seem to work out due to the ambigiuous nature of the problem.

- <b>PCA</b>: Seems to be the ordinary reduce dimensions and then compare against training data procedure. Not fantastically interesting.

- <b>Boosting</b>: Very vague description in this paragraph. Seems to describe a boosting approach to clustering or using hiearchial trees. Again problems with ambigiuity and lightning conditions.

-<b> Contour and silhouette matching</b>: Sort of a repitition of the detection chapter. Very much based on template matching again. Biggest problem is again ambiguity and clutter. There seems to be an idea to use the matching to restrict the area where the recognition is using contours and then use the silhouette to match. Again the approach is the obvious combine features...

- <b>Model-based recognition methods</b>. Starts out with some obvious statements such that the classification success depends on choosing the right features. Who would have known...They also cite some paper that has evaluated features and figured out that velocity features are...}
}

@inproceedings{Rother:2002wn,
author = {Rother, Carsten},
title = {{A new approach to vanishing point detection in architectural environments}},
booktitle = {Image and Vision Computing},
year = {2002},
pages = {647--655},
organization = {Royal Inst Technol, KTH, Computat Vis {\&} Act Percept Lab, CVAP, S-10044 Stockholm, Sweden}
}

@article{Donahue:2014ut,
author = {Donahue, Jeff and Hendricks, Lisa Anne and Guadarrama, Sergio and Rohrbach, Marcus and Venugopalan, Subhashini and Saenko, Kate and Darrell, Trevor J},
title = {{Long-term Recurrent Convolutional Networks for Visual Recognition and Description}},
journal = {arXiv.org},
year = {2014},
eprint = {1411.4389v3},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = nov
}

@inproceedings{Hu:2014eu,
author = {Hu, Junlin and Lu, Jiwen and Tan, Yap-Peng},
title = {{Discriminative Deep Metric Learning for Face Verification in the Wild}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on},
year = {2014},
pages = {1875--1882}
}

@article{Provost:2001tu,
author = {Provost, J and Beeson, P and Kuipers, Benjamin J},
title = {{Toward learning the causal layer of the spatial semantic hierarchy using SOMs}},
journal = {{\ldots} Symposium Workshop on Learning {\ldots}},
year = {2001},
annote = {Summary: 

Deals with SSH abstraction. Especiially the SSH causal layer. The causal layer deals with sensor views and control actions, and how they affect each other. They use a SOM(Self-organizing Maps) for representing the SSH view set. This fits in with modelling everything as an abstract graph. 

They have some good points in the SSH Causal Layer chapter of qualities of how to handle sensory input.  

First they define a triple of edges {\&}lt;V,A,V'{\&}gt; such that action A taken under view V indicates V' will happen.

They state that a robot must be able to recognize its current sensor input as one of its set of known views. This means that views must be clustered or at least be discriminated but this is too hard given the noisy input. Therefor they choose to formulate the problem as maximization of the predictive accurace of the {\&}lt;V,A,V'{\&}gt; relations, i.e., the confidence it will see the view V' after taking action A in view V. 

Take home message seems to be to reformulate the recognition problem as a relation maximization problem since then one does not have to deal with the infinite space of possible noisy inputs. 

<b>Relation to my work:</b> possibly how we can formulate the problem as relational problem rather than view causality learning problem. <b>This thought could be expanded upon.</b> 




}
}

@inproceedings{Dindo:2010fr,
author = {Dindo, H and Zambuto, D},
title = {{A probabilistic approach to learning a visually grounded language model through human-robot interaction}},
booktitle = {2010 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2010},
pages = {790--796}
}

@article{Hendrich:2014tz,
author = {Hendrich, N and Bernardino, A},
title = {{Affordance-Based Grasp Planning for Anthropomorphic Hands from Human Demonstration - Springer}},
journal = {ROBOT2013: First Iberian Robotics {\ldots}},
year = {2014}
}

@article{Thrun:2000jv,
author = {Thrun, Sebastian},
title = {{Probabilistic Algorithms and the Interactive Museum Tour-Guide Robot Minerva}},
journal = {The International Journal of Robotics Research},
year = {2000},
volume = {19},
number = {11},
pages = {972--999},
month = nov
}

@inproceedings{Steder:2011bm,
author = {Steder, B and Rusu, R B and Konolige, K and Burgard, Wolfram},
title = {{Point feature extraction on 3D range scans taking into account object boundaries}},
booktitle = {2011 IEEE International Conference on Robotics and Automation},
year = {2011},
pages = {2601--2608}
}

@article{Jaakkola:pDo29F5A,
author = {Jaakkola, Tommi S},
title = {{Jaakkola NIPS 2000 Tutorial}}
}

@inproceedings{Sahbani:2009hd,
author = {Sahbani, Anis and El-Khoury, Sahar},
title = {{A hybrid approach for grasping 3D objects}},
booktitle = {2009 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2009},
pages = {1272--1277},
annote = {
<b>Summary</b>
Segement perfect 3D object models using a segmentation algorithm based upon Gaussian curvature and concaveness. An object is represented using superquadratics.   The segementation is such that 7 differerent superquadratics are used for each object. 

They then label a superquadratic  for each object as the graspable part. They train a Neural Network on the labeled data.

To generate a grasps they do anlytical computations on the detected graspable part. The analytical parts are a force-closure test and a handkinematics test.

No real data is tested. Paper was before Kinect came out.




}
}

@article{Lazebnik:2005he,
author = {Lazebnik, S and Schmid, C and Ponce, J},
title = {{A sparse texture representation using local affine regions}},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
year = {2005},
volume = {27},
number = {8},
pages = {1265--1278}
}

@inproceedings{Claassens:2012kh,
author = {Claassens, J and Demiris, Y},
title = {{Exploiting affordance symmetries for task reproduction planning}},
booktitle = {Humanoid Robots (Humanoids), 2012 12th IEEE-RAS International Conference on},
year = {2012},
pages = {653--659}
}

@inproceedings{Kroemer:2012hi,
author = {Kroemer, O and Ugur, E and Oztop, E and Peters, J},
title = {{A kernel-based approach to direct action perception}},
booktitle = {2012 IEEE International Conference on Robotics and Automation},
year = {2012},
pages = {2605--2610}
}

@article{Kohli:2008wx,
author = {Kohli, Pushmeet and Rihan, J and Bray, M and Torr, PHS},
title = {{Simultaneous Segmentation and Pose Estimation of Humans Using Dynamic Graph Cuts - Springer}},
journal = {International Journal of Computer {\ldots}},
year = {2008}
}

@article{Remolina:2004km,
author = {Remolina, Emilio and Kuipers, Benjamin J},
title = {{Towards a general theory of topological maps}},
journal = {Artificial Intelligence Review},
year = {2004},
volume = {152},
number = {1},
pages = {47--104},
month = jan,
annote = {<b>Summary:</b> Too much toplogical map and logic stuff to be worth reading. Doubtful if it contains much information.}
}

@inproceedings{Kazemi:2014he,
author = {Kazemi, Vahid and Sullivan, Josephine},
title = {{One Millisecond Face Alignment with an Ensemble of Regression Trees}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on},
year = {2014},
pages = {1867--1874}
}

@article{Shlens:2014vi,
author = {Shlens, Jonathon},
title = {{A Tutorial on Principal Component Analysis}},
journal = {arXiv.org},
year = {2014},
month = apr
}

@inproceedings{Xue:2009vx,
author = {Xue, Zhixing and Kasper, A and Zoellner, J M and Dillmann, R},
title = {{An automatic grasp planning system for service robots}},
booktitle = {Advanced Robotics, 2009. ICAR 2009. International Conference on},
year = {2009},
pages = {1--6}
}

@inproceedings{Claassens:2011gp,
author = {Claassens, J and Demiris, Y},
title = {{Generalising human demonstration data by identifying affordance symmetries in object interaction trajectories}},
booktitle = {2011 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2011},
pages = {1980--1985}
}

@article{Ginestet:2010dd,
author = {Ginestet, Cedric},
title = {{Introduction to Statistical Relational Learning}},
journal = {Journal of the Royal Statistical Society: Series A (Statistics in Society)},
year = {2010},
volume = {173},
number = {4},
pages = {934--935},
month = sep
}

@article{Biederman:1987bx,
author = {Biederman, Irving},
title = {{Recognition-by-components: A theory of human image understanding.}},
journal = {Psychological review},
year = {1987},
volume = {94},
number = {2},
pages = {115--117}
}

@article{Cheng:2001kp,
author = {Cheng, H D and Jiang, X H and Sun, Y and Wang, Jingli},
title = {{Color image segmentation: advances and prospects}},
journal = {Pattern Recognition},
year = {2001},
volume = {34},
number = {12},
pages = {2259--2281},
month = dec
}

@article{He:2015vx,
author = {He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
title = {{Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification}},
journal = {arXiv.org},
year = {2015},
eprint = {1502.01852v1},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = feb
}

@article{Hastie:2000up,
author = {Hastie, T and Tibshirani, R and Eisen, M B and Alizadeh, A},
title = {{Gene shaving'as a method for identifying distinct sets of genes with similar expression patterns}},
journal = {Genome {\ldots}},
year = {2000}
}

@article{Torralba:2003im,
author = {Torralba, Antonio},
title = {{Contextual Priming for Object Detection - Springer}},
journal = {International Journal of Computer Vision},
year = {2003},
volume = {53},
number = {2},
pages = {169--191}
}

@article{Kruger:2011bj,
author = {Kr{\"u}ger, Norbert and Geib, Christopher and Piater, Justus and Petrick, Ronald and Steedman, Mark and W{\"o}rg{\"o}tter, Florentin and Ude, Ale{\v s} and Asfour, Tamim and Kraft, Dirk and Omr{\v c}en, Damir and Agostini, Alejandro and Dillmann, R{\"u}diger},
title = {{Object--Action Complexes: Grounded abstractions of sensory--motor processes}},
journal = {Robotics and Autonomous Systems},
year = {2011},
volume = {59},
number = {10},
pages = {740--757},
month = oct
}

@article{Tsai:uy,
author = {Tsai, G and Kuipers, Benjamin J},
title = {{Focusing Attention on Visual Features that Matter}},
journal = {eecs.umich.edu
}
}

@article{Chopra:2005jh,
author = {Chopra, Sumit and Hadsell, Raia and LeCun, Yann},
title = {{Learning a Similarity Metric Discriminatively, with Application to Face Verification.}},
journal = {CVPR},
year = {2005},
pages = {539--546}
}

@article{QuinoneroCandela:2005wp,
author = {Qui{\~n}onero-Candela, Joaquin and Rasmussen, Carl Edward},
title = {{A unifying view of sparse approximate Gaussian process regression}},
journal = {Journal of Machine Learning Research},
year = {2005},
volume = {6},
pages = {1939--1959}
}

@book{Bishop:2006ui,
author = {Bishop, Christopher M},
title = {{Pattern Recognition and Machine Learning}},
publisher = {Springer-Verlag New York, Inc.},
year = {2006}
}

@book{MacKay:b7_kxpTs,
author = {MacKay, David},
title = {{Information Theory, Inference, and Learning Algorithms}}
}

@inproceedings{Hendrich:2010hx,
author = {Hendrich, N and Klimentjew, D and Zhang, Jianwei},
title = {{Multi-sensor based segmentation of human manipulation tasks}},
booktitle = {Multisensor Fusion and Integration for Intelligent Systems (MFI), 2010 IEEE Conference on},
year = {2010},
pages = {223--229}
}

@article{Bernardo:2008tm,
author = {Bernardo, J M and Bayarri, M J and Berger, J O and Dawid, A P},
title = {{Density Modeling and Clustering Using Dirichlet Diffusion Trees}},
year = {2008}
}

@book{Laub:2005wt,
author = {Laub, Alan J},
title = {{Matrix Analysis for Scientists and Engineers}},
publisher = {Siam},
year = {2005}
}

@article{Csato:2002tz,
author = {Csat{\'o}, Lehel and Opper, Manfred},
title = {{Sparse on-line Gaussian processes}},
journal = {Neural Computation},
year = {2002},
volume = {14},
number = {3},
month = mar
}

@article{Welch:nModKeqF,
author = {Welch, Greg and Bishop, Gary},
title = {{An Introduction to the Kalman Filter}}
}

@article{Fox:1997ed,
author = {Fox, Dieter and Burgard, Wolfram and Thrun, Sebastian},
title = {{The dynamic window approach to collision avoidance}},
journal = {IEEE Robotics {\&} Automation Magazine},
year = {1997},
volume = {4},
number = {1},
pages = {23--33},
month = mar
}

@article{Ekvall:2005ue,
author = {Ekvall, S and Kragic, Danica},
title = {{Grasp Recognition for Programming by Demonstration}},
journal = {{\ldots} },
year = {2005}
}

@article{Ohagan:1994tw,
author = {O'hagan, Anthony and VEENSTRA, RH and Vanbatenburg and Pc and Pc},
title = {{Bayesian Discovery Sampling in Financial Auditing - a Hierarchical Prior Model for Substantive Test Sample Sizes}},
journal = {Statistician},
year = {1994},
volume = {43},
number = {1},
pages = {99--110}
}

@proceedings{Tighe:y1TUmcTG,
title = {{Finding Things: Image Parsing with Regions and Per-Exemplar Detectors}}
}

@article{Sahin:2007gr,
author = {Sahin, E and Cakmak, M and Dogar, M R and Ugur, E and Ucoluk, G},
title = {{To Afford or Not to Afford: A New Formalization of Affordances Toward Affordance-Based Robot Control}},
journal = {Adaptive Behavior},
year = {2007},
volume = {15},
number = {4},
pages = {447--472},
month = dec
}

@inproceedings{BarckHolst:2009uy,
author = {Barck-Holst, C and Ralph, M and Holmar, F and Kragic, Danica},
title = {{Learning grasping affordance using probabilistic and ontological approaches}},
booktitle = {Advanced Robotics, 2009. ICAR 2009. International Conference on},
year = {2009},
pages = {1--6}
}

@article{Tsai:2012vk,
author = {Tsai, G and Kuipers, Benjamin J},
title = {{Dynamic visual understanding of the local environment for an indoor navigating robot}},
journal = {Intelligent Robots and Systems (IROS)},
year = {2012}
}

@inproceedings{Detry:2012bp,
author = {Detry, Renaud and Ek, Carl Henrik and Madry, Marianna and Piater, Justus and Kragic, Danica},
title = {{Generalizing grasps across partly similar objects}},
booktitle = {2012 IEEE International Conference on Robotics and Automation},
year = {2012},
pages = {3791--3797},
publisher = {IEEE}
}

@techreport{Haines:EPp9vr3r,
author = {Haines, Tom},
title = {{Gaussian Conjugate Prior Cheat Sheet}}
}

@techreport{Schon:xcYovD6r,
author = {Sch{\"o}n, Thomas and Lindsten, Fredrik},
title = {{Manipulating the Multivariate Gaussian Density}}
}

@article{Ciocarlie:2009tn,
author = {Ciocarlie, Matei T and Allen, Peter K},
title = {{Hand Posture Subspaces for Dexterous Robotic Grasping}},
journal = {The International Journal of Robotics Research},
year = {2009},
annote = {<b>Second read.

Terms to look up</b> 
Passive Mechanical Adaption. 

<b>Thoughts</b> 
It is interesting that not many people seem to use heuristics when doing grasping etc. For example in the glass gripping case in fig2 after 7000 iterations the grasp has the thumb down, while a human if it would carry an object always would see too it to have the palm underneath the object unless you are to pick up the object and stab someone. Obviously grasping is inherintly task depedent. 

<b>Review</b>: 
Really good and well written paper; I can't judge the quality of the results though. 

The paper is divided into two sections. The first section researches lower dimensional representation of grasps using PCA. The lower dimensional grasps are then put into a cost function operating in lower dimensional space together with the mechanical constrains/readings of hand sensors. The cost function is then optimized with respect to the object targeted for grasping to find the best grip. I do not quite understand the exact way this is done. If there is predetermined point for gripping the object and the hand chooses the best one for that point. So for example if we are gripping a pole, then the authors have pre-set that we should grip in the middle; and so approaches with the hand and lets the method find the best grip.

The second part moves onto explore using a human to guide the hand to a good grip positioin i.e. wrist and position. The modified algorithm with a more easily calculated cost function then finds the best grip position.  
}
}

@article{Lauritzen:2009wz,
author = {Lauritzen, Steffen},
title = {{The Multivariate Gaussian Distribution}},
year = {2009},
pages = {1--22},
month = nov
}

@inproceedings{Fox:1999ws,
author = {Fox, Dieter and Burgard, Wolfram and Dellaert, F and Thrun, Sebastian},
title = {{Monte carlo localization: Efficient position estimation for mobile robots}},
booktitle = {Proceedings of the National {\ldots}},
year = {1999}
}

@inproceedings{Ekvall:2004gh,
author = {Ekvall, S and Kragic, Danica},
title = {{Interactive grasp learning based on human demonstration}},
booktitle = {Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on},
year = {2004},
pages = {3519--3524}
}

@article{BenAmor:2012da,
author = {Ben Amor, Heni and Kroemer, Oliver and Hillenbrand, Ulrich and Neumann, Gerhard and 0001, Jan Peters},
title = {{Generalization of human grasping for multi-fingered robot hands.}},
journal = {IROS},
year = {2012},
pages = {2043--2050}
}

@article{Goldfeder:2009uh,
author = {Goldfeder, C and Ciocarlie, Matei T and Dang, Hao},
title = {{The Columbia grasp database}},
journal = {Robotics, IEEE Transactions on},
year = {2009}
}

@article{Barrow:1977va,
author = {Barrow, H G and Tenenbaum, J M and Bolles, R C and Wolf, H C},
title = {{Parametric Correspondence and Chamfer Matching: Two New Techniques for Image Matching}},
year = {1977}
}

@article{Torrey:2009tu,
author = {Torrey, L and Shavlik, J},
title = {{Transfer Learning}},
journal = {Handbook of Research on Machine Learning {\ldots}},
year = {2009}
}

@article{DYKES:1996vd,
author = {DYKES, N},
title = {{A TANGLED WEB OF GUESSES}},
year = {1996}
}

@article{Ekvall:2006gy,
author = {Ekvall, S and Kragic, Danica},
title = {{Learning Task Models from Multiple Human Demonstrations}},
journal = {Robot and Human Interactive Communication, 2006. ROMAN 2006. The 15th IEEE International Symposium on},
year = {2006},
pages = {358--363}
}

@article{Pokorny:2013vv,
author = {Pokorny, Florian T and Hang, Kaiyu and Kragic, Danica},
title = {{Grasp Moduli Spaces.}},
journal = {Robotics Science and Systems 2013},
year = {2013}
}

@article{Stober:2008wu,
author = {Stober, J and Kuipers, Benjamin J},
title = {{From Pixels to Policies: A Bootstrapping Agent}},
journal = {{\ldots} and Learning},
year = {2008},
annote = {Incredibly densly written maybe this is a skipper?}
}

@article{Gevers:1997fp,
author = {Gevers, Theo and Smeulders, Arnold W M},
title = {{Color Based Object Recognition.}},
journal = {ICIAP},
year = {1997},
pages = {319--326}
}

@article{Damianou:2012wu,
author = {Damianou, Andreas C and Ek, Carl Henrik and Titsias, Michalis K and Lawrence, Neil D},
title = {{Manifold Relevance Determination}},
journal = {arXiv.org},
year = {2012},
volume = {cs.LG},
month = jun
}

@inproceedings{Flint:2011hh,
author = {Flint, A and Murray, D and Reid, I},
title = {{Manhattan scene understanding using monocular, stereo, and 3D features}},
booktitle = {Computer Vision (ICCV), 2011 IEEE International Conference on},
year = {2011},
pages = {2228--2235}
}

@article{Xiangxin:HLCf77Zg,
author = {Xiangxin, Zhu and Vondrick, Carl},
title = {{Do We Need More Training Data or Better
Models for Object Detection?}}
}

@article{Kulis:2012tx,
author = {Kulis, B},
title = {{Metric learning: A survey}},
journal = {Foundations and Trends in Machine Learning},
year = {2012}
}

@article{Boyle:2005vi,
author = {Boyle, P and Frean, M},
title = {{Multiple output gaussian process regression}},
year = {2005},
annote = {Thoughts: Will be very interesting to see results from this and if any people has extended or referenced this paper. If this would be incorporated in my variational GPLVM approach that would be kind of awesome. 

Review:

Handles multiple GP outputs. They treat the GP as white noise sources convolved with smoothing kernels and parametrize the kernels instead and thereby manage to handle multiple coupled GP outputs. }
}

@inproceedings{Beetz:2010bu,
author = {Beetz, Michael and M{\"o}senlechner, Lorenz and Tenorth, Moritz},
title = {{CRAM - A Cognitive Robot Abstract Machine for everyday manipulation in human environments}},
booktitle = {2010 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2010},
pages = {1012--1017},
publisher = {IEEE}
}

@book{Hartley:2000un,
author = {Hartley, Richard and Zisserman, Andrew},
title = {{Multiple view geometry in computer vision}},
publisher = {Cambridge Univ Press},
year = {2000},
volume = {2}
}

@inproceedings{Przybylski:2010kl,
author = {Przybylski, M and Asfour, Tamin and Dillmann, R},
title = {{Unions of balls for shape approximation in robot grasping}},
booktitle = {2010 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2010},
pages = {1592--1599}
}

@article{Fox:2011cq,
author = {Fox, Dieter and Burgard, Wolfram and Thrun, Sebastian},
title = {{Markov Localization for Mobile Robots in Dynamic Environments}},
journal = {arXiv.org},
year = {2011},
eprint = {1106.0222v1},
eprinttype = {arxiv},
eprintclass = {cs.AI},
month = jun
}

@proceedings{Lin:ABCnZPwM,
title = {{Grasp Planning Based on Strategy Extracted from Demonstration}}
}

@article{Vernon:2007jj,
author = {Vernon, David and Metta, Giorgio and Sandini, Giulio},
title = {{A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computational Agents.}},
journal = {IEEE Trans. Evolutionary Computation ()},
year = {2007},
volume = {11},
number = {2},
pages = {151--180}
}

@article{Lee:1999gw,
author = {Lee, Daniel D and Seung, H Sebastian},
title = {{Learning the parts of objects by non-negative matrix factorization}},
journal = {Nature},
year = {1999},
volume = {401},
number = {6755},
pages = {788--791},
month = oct
}

@book{Duda:2012uw,
author = {Duda, Richard O and Hart, Peter E and Stork, David G},
title = {{Pattern Classification}},
publisher = {John Wiley {\&} Sons},
year = {2012},
month = nov
}

@article{Thomaz:2004hz,
author = {Thomaz, Carlos E and Gillies, D F and Feitosa, R Q},
title = {{A new covariance estimate for Bayesian classifiers in biometric recognition}},
journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
year = {2004},
volume = {14},
number = {2},
pages = {214--223}
}

@article{Nikandrova:2015uu,
author = {Nikandrova, E and Kyrki, V},
title = {{Category-based task specific grasping}},
journal = {Robotics and Autonomous Systems},
year = {2015}
}

@article{Chu:ud,
author = {Chu, V and McMahon, I and Riano, L and McDonald, C G and He, Q},
title = {{Using Robotic Exploratory Procedures to Learn the Meaning of Haptic Adjectives}},
journal = {eecs.berkeley.edu
}
}

@article{Lawrence:2004vc,
author = {Lawrence, Neil D},
title = {{Matching kernels through Kullback-Leibler divergence minimization}},
year = {2004}
}

@inproceedings{Mason:2011wo,
author = {Mason, M and Lopes, M},
title = {{Robot self-initiative and personalization by learning through repeated interactions}},
booktitle = {Human-Robot Interaction (HRI), 2011 6th ACM/IEEE International Conference on},
year = {2011},
pages = {433--440}
}

@article{Laidler:2005ws,
author = {Laidler, J and Lawrence, Neil D},
title = {{A Probabilistic Approach to Spectral Clustering: Using KL Divergence to Find Good Clusters}},
year = {2005}
}

@inproceedings{Pinto:2009iu,
author = {Pinto, Nicolas and DiCarlo, James J and Cox, David D},
title = {{How far can you get with a modern face recognition test set using only simple features?}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2009 IEEE Conference on},
year = {2009},
pages = {2591--2598},
publisher = {IEEE}
}

@article{Sherman:1950vq,
author = {Sherman, J and Morrison, W J},
title = {{Adjustment of an Inverse Matrix Corresponding to A Change in One Element of a Given Matrix}},
journal = {The Annals of Mathematical Statistics},
year = {1950},
annote = {Contains a basic formula for updating a matrix inverse corresponding to a change in one element of the given matrix.}
}

@article{Kazemi:uw,
author = {Kazemi, Vahid and Sullivan, Josephine},
title = {{Using Richer Models for Articulated Pose Estimation of Footballers}},
journal = {bmva.org
}
}

@inproceedings{Ijspeert:2002jj,
author = {Ijspeert, Auke J and Nakanishi, J and Schaal, Stefan},
title = {{Movement imitation with nonlinear dynamical systems in humanoid robots}},
booktitle = {2002 IEEE International Conference on Robotics and Automation},
year = {2002},
pages = {1398--1403}
}

@article{Yang:2012tz,
author = {Yang, W and Wang, Y and Vahdat, A and Mori, G},
title = {{Kernel Latent SVM for Visual Recognition}},
journal = {Advances in Neural Information {\ldots}},
year = {2012}
}

@article{Stoytchev:2005il,
author = {Stoytchev, Alexander},
title = {{Behavior-Grounded Representation of Tool Affordances.}},
journal = {ICRA},
year = {2005},
pages = {3060--3065}
}

@article{Kedem:wp,
author = {Kedem, D and Xu, Z E and Weinberger, K Q},
title = {{Gradient Boosted Large Margin Nearest Neighbors}},
journal = {cse.wustl.edu
}
}

@book{Corke:2011wm,
author = {Corke, Peter},
title = {{Robotics, Vision and Control}},
publisher = {Springer Verlag},
year = {2011},
series = {Fundamental Algorithms in MATLAB},
month = nov,
annote = {Stuff I should read according to Renaud: 

2, 5, -6-, 7.1, 7.2, 10, 12, 13
}
}

@article{Triebel:ws,
author = {Triebel, HGRPR and Posner, I},
title = {{Knowing When We Don't Know: Introspective Classification for Mission-Critical Decision Making}},
journal = {robots.ox.ac.uk
}
}

@inproceedings{Chan:2014ip,
author = {Chan, W P and Kakiuchi, Y and Okada, K and Inaba, M},
title = {{Determining proper grasp configurations for handovers through observation of object movement patterns and inter-object interactions during usage}},
booktitle = {Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on},
year = {2014},
pages = {1355--1360}
}

@article{Kedem:2012wv,
author = {Kedem, Dor and Tyree, Stephen and Weinberger, Kilian Q and Sha, Fei and Lanckriet, Gert R G},
title = {{Non-linear Metric Learning.}},
journal = {NIPS},
year = {2012},
pages = {2582--2590}
}

@inproceedings{Tenorth:2009hv,
author = {Tenorth, Mori and Beetz, Michael},
title = {{KNOWROB --- Knowledge Processing for Autonomous Personal Robots}},
booktitle = {2009 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2009},
pages = {4261--4266},
publisher = {IEEE}
}

@article{Kruger:2002hn,
author = {Kr{\"u}ger, Norbert and Ackermann, Marcus and Sommer, Gerald},
title = {{Accumulation of object representations utilising interaction of robot action and perception}},
journal = {Knowledge-Based Systems},
year = {2002},
volume = {15},
number = {1-2},
pages = {111--118},
month = jan
}

@article{Fox:2003jj,
author = {Fox, Dieter and Hightower, Jeffrey and Liao, Lin and Schulz, D and Borriello, G},
title = {{Bayesian filtering for location estimation}},
journal = {Pervasive Computing, IEEE},
year = {2003},
volume = {2},
number = {3},
pages = {24--33},
annote = {<b>Review / Summary:</b>
Paper goes through filtering tecchniques for finding persons position in a mapped environment. They evaluate several different Bayesian filtering techniques such as Kalman, Particle etc. and a couple of techniques for data representation.

Not very interesting. Not very conclusive. I don't understand why this paper has so many citations? I guess it is a review paper. Still though, I wouldn't want to publish this.}
}

@article{Roweis:1999ul,
author = {Roweis, Sam and Ghahramani, Zoubin},
title = {{A unifying review of linear gaussian models}},
journal = {Neural Computation},
year = {1999},
volume = {11},
number = {2},
pages = {305--345}
}

@article{Fox:2000fy,
author = {Fox, Dieter and Burgard, Wolfram and Kruppa, Hannes and Thrun, Sebastian},
title = {{A Probabilistic Approach to Collaborative Multi-Robot Localization}},
journal = {Autonomous Robots},
year = {2000},
volume = {8},
number = {3},
pages = {325--344}
}

@article{Torresani:2006wb,
author = {Torresani, Lorenzo and Lee, Kuang-chih},
title = {{Large Margin Component Analysis.}},
journal = {NIPS},
year = {2006},
pages = {1385--1392}
}

@article{Gammerman:1998ul,
author = {Gammerman, Alex and Vovk, Volodya and Vapnik, Vladimir Naumovich},
title = {{Learning by Transduction}},
journal = {arXiv.org},
year = {1998},
eprint = {1301.7375v1},
eprinttype = {arxiv},
eprintclass = {cs.LG},
pages = {148--155},
month = jul
}

@article{Peng:2014kn,
author = {Peng, Xiaojiang and Qiao, Yu and Peng, Qiang and Wang, Qionghua},
title = {{Large Margin Dimensionality Reduction for Action Similarity Labeling}},
journal = {IEEE Signal Processing Letters},
year = {2014},
volume = {21},
number = {8},
pages = {1022--1025}
}

@article{Rosenthal:2000tr,
author = {Rosenthal, Jeffrey S},
title = {{Parallel computing and Monte Carlo algorithms}},
journal = {Far East Journal of Theoretical Statistics},
year = {2000},
pages = {207--236},
month = mar
}

@book{Koller:xo9XAvqw,
author = {Koller, Daphne},
title = {{Probabilistic Graphical Models}},
publisher = {The MIT Press},
annote = {5, 104, 296, 297, 360, 378}
}

@article{Agarwal:2004bb,
author = {Agarwal, S and Awan, A and Roth, D},
title = {{Learning to detect objects in images via a sparse, part-based representation}},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
year = {2004},
volume = {26},
number = {11},
pages = {1475--1490}
}

@article{Weinberger:2008ho,
author = {Weinberger, Kilian Q and Saul, Lawrence K},
title = {{Fast solvers and efficient implementations for distance metric learning.}},
journal = {ICML},
year = {2008},
pages = {1160--1167}
}

@book{Prince:2012ud,
author = {Prince, Simon J D},
title = {{Computer Vision}},
publisher = {Cambridge University Press},
year = {2012},
series = {Models, Learning, and Inference},
month = jun
}

@article{Hunter:2009vf,
author = {Hunter, John},
title = {{Lecture Notes On Applied Mathematics}},
year = {2009},
pages = {1--178},
month = jun
}

@article{Rosasco:2004cg,
author = {Rosasco, Lorenzo and De Vito, Ernesto and Caponnetto, Andrea and Piana, Michele and Verri, Alessandro},
title = {{Are Loss Functions All the Same?.}},
journal = {Neural Computation},
year = {2004},
volume = {16},
number = {5},
pages = {1063--107}
}

@inproceedings{Rennie:2005un,
author = {Rennie, JDM and Srebro, N},
title = {{Loss functions for preference levels: Regression with discrete ordered labels}},
booktitle = {Proceedings of the IJCAI multidisciplinary {\ldots}},
year = {2005}
}

@article{POSNER:1967ef,
author = {Posner, Michael I and Goldsmith, Ralph and Welton, Kenneth E Jr},
title = {{Perceived Distance And The Classification Of Distorted Patterns.}},
journal = {Journal of Experimental Psychology},
year = {1967},
volume = {73},
number = {1},
pages = {28--38}
}

@article{Biederman:1982fa,
author = {Biederman, Irving and Mezzanotte, Robert J and Rabinowitz, Jan C},
title = {{Scene perception: Detecting and judging objects undergoing relational violations}},
journal = {Cognitive psychology},
year = {1982},
volume = {14},
number = {2},
pages = {143--177},
month = apr
}

@article{Arnold:2007hp,
author = {Arnold, Andrew and Nallapati, Ramesh and Cohen, William W},
title = {{A Comparative Study of Methods for Transductive Transfer Learning}},
journal = {Carroll, James L},
year = {2007}
}

@article{Xue:2012tk,
author = {Xue, Z and R{\"u}hl, S W and Z{\"o}llner, J M and Dillmann, R},
title = {{An Automatic Grasp Planning System for Multi-fingered Robotic Hands - Springer}},
journal = {Towards Service Robots for {\ldots}},
year = {2012}
}

@article{Hu:1999gn,
author = {Hu, G Y and O'Connell, R F},
title = {{Analytical inversion of symmetric tridiagonal matrices}},
journal = {Journal of Physics A: Mathematical and General},
year = {1999},
volume = {29},
number = {7},
pages = {1511--1513},
month = jan
}

@article{Calli:2015tv,
author = {Calli, Berk and Walsman, Aaron and Singh, Arjun and Srinivasa, Siddhartha and Abbeel, Pieter and Dollar, Aaron M},
title = {{Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols}},
journal = {arXiv.org},
year = {2015},
eprint = {1502.03143v1},
eprinttype = {arxiv},
eprintclass = {cs.RO},
month = feb
}

@inproceedings{Fergus:2005co,
author = {Fergus, R and Fei-Fei, L and Perona, P and Zisserman, Andrew},
title = {{Learning object categories from Google's image search}},
booktitle = {Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1},
year = {2005},
pages = {1816--1823 Vol. 2},
publisher = {IEEE}
}

@article{Bohg:2011bb,
author = {Bohg, Jeannette and Johnson-Roberson, Matthew and Le{\'o}n, Beatriz and Felip, Javier and Gratal, Xavi and Bergstr{\"o}m, Niklas and Kragic, Danica and Morales, Antonio},
title = {{Mind the gap - robotic grasping under incomplete observation.}},
journal = {ICRA},
year = {2011},
pages = {686--693}
}

@article{Hazan:2012tl,
author = {Hazan, Tamir and Jaakkola, Tommi S},
title = {{On the Partition Function and Random Maximum A-Posteriori Perturbations}},
journal = {arXiv.org},
year = {2012},
eprint = {1206.6410v1},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = jun,
annote = {Appears in Proceedings of the 29th International Conference on
  Machine Learning (ICML 2012)}
}

@article{Fox:2003tg,
author = {Fox, Dieter},
title = {{Adapting the sample size in particle filters through KLD-sampling}},
year = {2003}
}

@article{Hariharan:2014wq,
author = {Hariharan, Bharath and Arbel{\'a}ez, Pablo and Girshick, Ross and Malik, Jitendra},
title = {{Hypercolumns for Object Segmentation and Fine-grained Localization}},
journal = {arXiv.org},
year = {2014},
eprint = {1411.5752v1},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = nov,
annote = {CVPR Submission}
}

@inproceedings{Sorokin:2010dz,
author = {Sorokin, A and Berenson, D and Srinivasa, S S and Hebert, M},
title = {{People helping robots helping people: Crowdsourcing for grasping novel objects}},
booktitle = {2010 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2010},
pages = {2117--2122}
}

@inproceedings{Thrun:2005il,
author = {Thrun, Sebastian and Wegbreit, B},
title = {{Shape from symmetry}},
booktitle = {Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on},
year = {2005},
pages = {1824--1831}
}

@book{Cover:2006ub,
author = {Cover, Thomas M and Thomas, Joy A},
title = {{Elements of Information Theory}},
publisher = {Wiley-Interscience},
year = {2006},
month = jul
}

@book{Taylor:aVTIVA2r,
author = {Taylor, Jay},
title = {{Markov Decision Processes: Lecture Notes for STP 425}}
}

@article{Snelson:2006vi,
author = {Snelson, Edward and Ghahramani, Zoubin},
title = {{Sparse Gaussian Processes using Pseudo-inputs}},
year = {2006}
}

@article{Quintero:2013wv,
author = {Quintero, C P and Fomena, R T and Shademan, A},
title = {{SEPO: Selecting by Pointing as an Intuitive Human-Robot Command Interface}},
journal = {IEEE Int Conference {\ldots}},
year = {2013}
}

@article{Kim:2013fk,
author = {Kim, Minyoung and Torre, Fernando},
title = {{Multiple instance learning via Gaussian processes}},
journal = {Data Mining and Knowledge Discovery},
year = {2013},
month = jul
}

@inproceedings{madry2013IROS,
author = {Madry, Marianna and Afkham, Heydar Maboudi and Ek, Carl Henrik and Carlsson, Stefan and Kragic, Danica},
title = {{Extracting the Essential Local Object Characteristics for 3D Object Categorization}},
booktitle = {IEEE International Conference on Intelligent Robots and Systems (IROS)},
year = {2013},
month = nov,
annote = {Summary:
Take a set of objects. Categorize them. Train a classifier on each of the categories.


To appear}
}

@book{Rudinac:2013ck,
author = {Rudinac, M},
title = {{Exploration and Learning for Cognitive Robots }},
publisher = {TU Delft, Delft University of Technology},
year = {2013},
month = jan
}

@article{Snelson:2006uk,
author = {Snelson, Edward},
title = {{Tutorial: Gaussian process models for machine learning}},
journal = {Gatsby Computational Neuroscience Unit},
year = {2006}
}

@inproceedings{Kulis:2011kw,
author = {Kulis, B and Saenko, K and Darrell, Trevor J},
title = {{What you saw is not what you get: Domain adaptation using asymmetric kernel transforms}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on},
year = {2011},
pages = {1785--1792}
}

@inproceedings{Rosales:2001el,
author = {Rosales, R and Athitsos, V and Sigal, L and Sclaroff, S},
title = {{3D Hand Pose Reconstruction Using Specialized Mappings }},
booktitle = {Eighth IEEE International Conference on Computer Vision},
year = {2001},
pages = {378--385},
publisher = {IEEE Comput. Soc},
annote = {<b>Second read.

Thoughts:</b>
Authors mentions that most approaches(10yrs ago) use a matching approach i.e. matching the current hand pose to a number of predefined handposes. The authors remarks that hand pose estimation is not viewpoint invariant which makes the whole case a hard nut to crack...They also mention a paper by Wu et al. that uses a sort of brute force approach by comparing to multiple viewpoints. Basically a discrete 360 matching it seems.  

<b>Terms to check:</b> 
Stochastic  visual segmentation, Hu moments(which seems to be functions of central image moments), 


<b>Review:</b>
The problem formulations for the authors is to automatically find the 3D hand pose from a monocular color sequence for every frame in that sequence. Positive characteristics of the author's system are no restriction on hand shapes, no manual initilization, view-point independence and good error recovery. 

To them the pose tracking problem is a regression problem. Since the matching of a monocular feature vector is a many to one problem due to pose problem not being viewpoit invariant i.e. the image seen in 2D could map to the same 3D model depending on which viewpoint one chooses. To solve this they train a probabilistic mixture of functions via the EM algorithm. The functions take visual features and give the DOF of the 3D hand model. The functions are a 1 layer of NN. After the function training is done a feedback function is trained to find the function that produces the best matching to the features, basically a function inverse if I understood it right. The inverse functions give 3D hand hypothesises that are measured in a energy function to pick out the best hypothesis.

The hands are tracked using skincolor. They have a smart approach to the first detection. Instead of detecting the hands they detect the face since face detections is more robust, and then they use the skincolor in the face to find the skincolor patches in the image and then the hands. There is a problem with occlusion in which the method fails. 

The features they use I think are just PCA of viewpoints of the 3D hands they have generated.

There are a lot of things that are bit weird here. I think mainly the explanation of the SMA and its mixture of probabilistic and deterministic. Further on the future process is a bit difuse. They don't mention speed either.      
Basically the paper seems like the first of a two part sequal.


}
}

@article{Rennie:2005ds,
author = {Rennie, Jason D M and Srebro, Nathan},
title = {{Fast maximum margin matrix factorization for collaborative prediction.}},
journal = {ICML},
year = {2005},
pages = {713--719}
}

@article{Gibbs:te,
author = {Gibbs, M N and MacKay, David},
title = {{Variational Gaussian process classifiers}},
journal = {Neural Networks, IEEE Transactions on},
volume = {11},
number = {6}
}

@article{Lawrence:2005vk,
author = {Lawrence, Neil D},
title = {{Probabilistic non-linear principal component analysis with Gaussian process latent variable models}},
journal = {Journal of Machine Learning Research},
year = {2005},
volume = {6},
pages = {1783--1816}
}

@article{Le:2011td,
author = {Le, Quoc V and Ranzato, Marc'Aurelio and Monga, Rajat and Devin, Matthieu and Chen, Kai and Corrado, Greg S and Dean, Jeff and Ng, Andrew Y.},
title = {{Building high-level features using large scale unsupervised learning}},
journal = {arXiv.org},
year = {2011},
month = dec
}

@article{Yianilos:1993vh,
author = {Yianilos, Peter N},
title = {{Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces.}},
journal = {SODA},
year = {1993},
pages = {311--321}
}

@book{Gut:2009td,
author = {Gut, Allan},
title = {{An Intermediate Course in Probability (Springer Texts in Statistics)}},
publisher = {Springer},
year = {2009},
edition = {2nd ed.},
month = jun
}

@article{Athitsos:2001td,
author = {Athitsos, V and Sclaroff, S},
title = {{3D Hand Pose Estimation by Finding Appearance-Based Matches in a Large Database of Training Views}},
year = {2001},
annote = {<b>Second read.</b>

<b>Keywords to check</b>  
Appearance based methods, Chamfer distance, dense sampling


<b>General thoughts</b>
- When you generate the database of possible poses which poses should have the database contain? One could probably take out a lot of clenched fists poses since some are so unlikely.
- I don't understand why they don't cluster the data in some sense. I mean comparing against a gigantic database is all fine but categorizing the poses and then comparing the images against a much denser subset would grant you much finer granularity and better matches. GPLVM clustering!
- On this there is also the Chamfer system way of doing things. Basically grouping similar templates and ordering them in a decision tree. See here for more http://www.gavrila.net/Research/Chamfer_System/chamfer_system.html
- There's also an interesting idea about contour protusions "whose length/width ratio exceeds a threshold" are to be detected as fingers which means even more discrimination could be determined. 

<b>Review</b>
Monocular 3D hand pose estimation.
The basic approach of this paper for hand pose recognition is to match the 3D hand to a gigantic database of 3D hand images using canny edges. It also discusses how to create the 3D hand dataset and good measures for similarity. They also discuss how a real time implementation would look like. The way the authors approach real life application is by skincolor detection and constrained backgrounds etc. i.e. again skimping away from the actual task of doing this effin unconstrained.

They start out by modeling the hand using 16 links this leads to 20 DOF, this means they don't take into consideration any wrist movements and such. Seemingly they don't deal with detecting the hand in a full image but seem to do the estimation against bounding boxed edges of hands. They also assume the size of the hand is fixed meaning that they have no moving camera. 

They generate all their training data by a 3D program - first they decide how many poses they should use(400-50000) and then they generate about 90 viewpoints of each pose. 

The inference is done via comparing canny edges using the so called Chamfer distance. I have no idea if the Chamfer distance is a good metric for edge image distances. If the true hand pose is contained in the top ten neighbouring images suggested by the metric then they consider the right pose has been estimated. }
}

@inproceedings{Civera:2011jl,
author = {Civera, J and Galvez-Lopez, D and Riazuelo, L and Tardos, J D and Montiel, J M M},
title = {{Towards semantic SLAM using a monocular camera}},
booktitle = {2011 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2011},
pages = {1277--1284}
}

@article{Goldfeder:2011kr,
author = {Goldfeder, Corey and Allen, Peter K},
title = {{Data-driven grasping}},
journal = {Autonomous Robots},
year = {2011},
volume = {31},
number = {1},
pages = {1--20},
month = apr
}

@inproceedings{Hart:1992dd,
author = {Hart, G W},
title = {{Nonintrusive appliance load monitoring}},
booktitle = {Proceedings of the IEEE},
year = {1992},
pages = {1870--1891}
}

@proceedings{Stark:2008bx,
title = {{Functional Object Class Detection Based on Learned Affordance Cues}},
year = {2008},
publisher = {Springer Berlin Heidelberg},
address = {Berlin, Heidelberg}
}

@inproceedings{Pelossof:2004ck,
author = {Pelossof, R and Miller, A and Allen, P and Jebara, T},
title = {{An SVM learning approach to robotic grasping}},
booktitle = {IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004},
year = {2004},
pages = {3512--3518 Vol.4},
publisher = {IEEE}
}

@article{Hjelm:2015hw,
author = {Hjelm, Martin and Ek, Carl Henrik and Detry, Renaud and Kragic, Danica},
title = {{Learning Human Priors for Task-Constrained Grasping.}},
journal = {ICVS},
year = {2015},
pages = {207--217}
}

@article{JieSun:2010kv,
author = {Jie Sun and Moore, J L and Bobick, A and Rehg, J M},
title = {{Learning Visual Object Categories for Robot Affordance Prediction}},
journal = {The International Journal of Robotics Research},
year = {2010},
volume = {29},
number = {2-3},
pages = {174--197},
month = mar
}

@book{Trench:czRvqTB1,
author = {Trench, William F},
title = {{Introduction to Real Analysis}}
}

@article{Sra:2012wt,
author = {Sra, S},
title = {{Scalable nonconvex inexact proximal splitting}},
journal = {Advances in Neural Information Processing Systems {\ldots}},
year = {2012}
}

@book{LaValle:2006wu,
author = {LaValle, Steven Michael},
title = {{Planning algorithms}},
publisher = {Cambridge university press},
year = {2006}
}

@article{Dogar:2000ba,
author = {Dogar, M and Srinivasa, S},
title = {{A Framework for Push-Grasping in Clutter}},
journal = {ieeexplore.ieee.org
},
year = {2000},
pages = {65--72},
month = jan
}

@article{Wilson:2015wv,
author = {Wilson, Andrew Gordon and Dann, Christoph and Lucas, Christopher G and Xing, Eric P},
title = {{The Human Kernel}},
journal = {arXiv.org},
year = {2015},
eprint = {1510.07389v3},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = oct,
annote = {11 pages, 5 figures. To appear in Neural Information Processing
  Systems (NIPS) 2015. Version 2: Figure 2 (i)-(n) now displays the second set
  of progressive function learning experiments}
}

@inproceedings{Urtasun:2008ec,
author = {Urtasun, Raquel and Fleet, David J and Geiger, Andreas and Popovi{\'c}, Jovan and Darrell, Trevor J and Lawrence, Neil D},
title = {{Topologically-constrained latent variable models}},
booktitle = {ICML '08: Proceedings of the 25th international conference on Machine learning},
year = {2008},
publisher = { ACM},
month = jul
}

@article{Herzog:2008te,
author = {Herzog, D and Kr{\"u}ger, V and Grest, D},
title = {{Parametric Hidden Markov Models for Recognition and Synthesis of Movements}},
journal = {BMVC},
year = {2008}
}

@article{Paolini:2012uq,
author = {Paolini, R and Rodriguez, A and Srinivasa, S and Mason, M T},
title = {{A Data-Driven Statistical Framework for Post-Grasp Manipulation}},
year = {2012}
}

@article{RSSB:RSSB503,
author = {Zou, Hui and Hastie, Trevor},
title = {{Regularization and variable selection via the elastic net}},
journal = {Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
year = {2005},
volume = {67},
number = {2},
pages = {301--320}
}

@inproceedings{Cimpoi:2015eg,
author = {Cimpoi, Mircea and Maji, Subhransu and Vedaldi, Andrea},
title = {{Deep filter banks for texture recognition and segmentation}},
booktitle = {2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR},
year = {2015},
pages = {3828--3836},
publisher = {IEEE}
}

@article{Harnad:2005tj,
author = {Harnad, Stevan},
title = {{To Cognize is to Categorize: Cognition is Categorization}},
journal = {Handbook of categorization in cognitive science},
year = {2005}
}

@article{Jansen:2006ie,
author = {Jansen, Bart and Belpaeme, Tony},
title = {{A computational model of intention reading in imitation}},
journal = {Robotics and Autonomous Systems},
year = {2006},
volume = {54},
number = {5},
pages = {394--402},
month = may
}

@article{Sontag:2008wd,
author = {Sontag, D and Meltzer, T and Globerson, A and Jaakkola, Tommi S},
title = {{Tightening LP Relaxations for MAP using Message Passing}},
year = {2008}
}

@article{Wilson:2012tx,
author = {Wilson, A and Fern, A and Tadepalli, P},
title = {{A Bayesian Approach for Policy Learning from Trajectory Preference Queries}},
journal = {Advances in Neural Information {\ldots}},
year = {2012}
}

@article{Chang:2010vi,
author = {Chang, M W and Srikumar, V},
title = {{Structured output learning with indirect supervision}},
journal = {Machine Learning},
year = {2010}
}

@article{Yu:2010tj,
author = {Yu, H F and Lo, H Y and Hsieh, H P and Lou, J K},
title = {{Feature engineering and classifier ensemble for KDD cup 2010}},
journal = {{\ldots} of the KDD Cup 2010 {\ldots}},
year = {2010}
}

@article{Vedaldi:2012tu,
author = {Vedaldi, A and Zisserman, Andrew},
title = {{Sparse kernel approximations for efficient classification and detection}},
journal = {Computer Vision and Pattern  {\ldots}},
year = {2012}
}

@inproceedings{Brunette:2009cl,
author = {Brunette, E S and Flemmer, R C and Flemmer, C L},
title = {{A review of artificial intelligence}},
booktitle = {Autonomous Robots and Agents, 2009. ICARA 2009. 4th International Conference on},
year = {2009},
pages = {385--392}
}

@inproceedings{Przybylski:2011hi,
author = {Przybylski, M and Asfour, Tamin and Dillmann, R},
title = {{Planning grasps for robotic hands using a novel object representation based on the medial axis transform}},
booktitle = {2011 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2011},
pages = {1781--1788}
}

@webpage{Duchi:aO5Fal05,
author = {Duchi, John and Tarlow, Daniel and Elidan, Gal and Koller, Daphne},
title = {{Using Combinatorial Optimization within Max-Product Belief Propagation}},
url = {http://www.cs.berkeley.edu/~jduchi/projects/DuchiTaKo06.html}
}

@article{Kondor:2005vy,
author = {Kondor, IR and Cs{\'a}nyi, G and Ahnert, SE},
title = {{Multi Facet Learning in Hilbert Spaces}},
year = {2005}
}

@article{Yewdell:2008it,
author = {Yewdell, Jonathan W},
title = {{How to succeed in science: a concise guide for young biomedical scientists. Part I: taking the plunge}},
journal = {Nature Reviews Molecular Cell Biology},
year = {2008},
volume = {9},
number = {5},
pages = {413--416},
month = may
}

@inproceedings{Varol:gd,
author = {Varol, Aydin and Salzmann, Mathieu and Fua, Pascal and Urtasun, Raquel},
title = {{2012 IEEE Conference on Computer Vision and Pattern Recognition}},
booktitle = {2012 IEEE Conference on Computer Vision and Pattern Recognition},
pages = {2248--2255},
publisher = {IEEE}
}

@article{Erren:2007vq,
author = {Erren, Thomas C and Cullen, Paul and Erren, Michael and Bourne, Philip E},
title = {{Ten Simple Rules for Doing Your Best Research, According to Hamming}},
journal = {PLoS Computational Biology},
year = {2007},
volume = {3},
number = {10},
pages = {e213}
}

@article{Billard:2004js,
author = {Billard, Aude and Epars, Yann and Calinon, Sylvain and Schaal, Stefan and Cheng, Gordon},
title = {{Discovering optimal imitation strategies}},
journal = {Robotics and Autonomous Systems},
year = {2004},
volume = {47},
number = {2-3},
pages = {69--77},
month = jun
}

@inproceedings{Fritz:2006kh,
author = {{Fritz} and {Paletta} and {Breithaupt} and {Rome}},
title = {{Learning Predictive Features in Affordance based Robotic Perception Systems}},
booktitle = {Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on},
year = {2006},
pages = {3642--3647}
}

@article{Petersen:2008up,
author = {Petersen, KB and Pedersen, MS},
title = {{The Matrix Cookbook}},
journal = {Version: November},
year = {2008},
volume = {14}
}

@inproceedings{Urtasun:2007ds,
author = {Urtasun, Raquel and Darrell, Trevor J},
title = {{Discriminative Gaussian Process Latent Variable Model for Classification}},
booktitle = {ICML '07: Proceedings of the 24rd international conference on Machine learning},
year = {2007},
pages = {927--934},
publisher = {ACM Press},
address = {New York, New York, USA}
}

@article{Kekale:2009he,
author = {Kek{\"a}le, Tauno and Weerd-Nederhof, Petra de and Cervai, Sara and Borelli, Massimo},
title = {{The ``dos and don'ts'' of writing a journal article}},
journal = {Journal of Workplace Learning},
year = {2009},
volume = {21},
number = {1},
pages = {71--80}
}

@article{Vinyals:2014uh,
author = {Vinyals, Oriol and Kaiser, Lukasz and Koo, Terry and Petrov, Slav and Sutskever, Ilya and Hinton, Geoffrey},
title = {{Grammar as a Foreign Language}},
journal = {arXiv.org},
year = {2014},
eprint = {1412.7449v3},
eprinttype = {arxiv},
eprintclass = {cs.CL},
month = dec
}

@article{He:2015tt,
author = {He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
title = {{Deep Residual Learning for Image Recognition}},
journal = {arXiv.org},
year = {2015},
eprint = {1512.03385v1},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = dec,
annote = {Tech report}
}

@inproceedings{Delage:2006jc,
author = {Delage, E and Lee, Honglak and Ng, Andrew Y.},
title = {{A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2006 IEEE Conference on},
year = {2006},
pages = {2418--2428}
}

@article{HernandezLobato:2015vs,
author = {Hern{\'a}ndez-Lobato, Jos{\'e} Miguel and Gelbart, Michael A and Hoffman, Matthew W and Adams, Ryan P and Ghahramani, Zoubin},
title = {{Predictive Entropy Search for Bayesian Optimization with Unknown Constraints.}},
journal = {ICML},
year = {2015},
volume = {stat.ML},
pages = {1699--1707}
}

@article{Weinberger:2005to,
author = {Weinberger, K Q and Blitzer, J and Saul, Lawrence K},
title = {{Distance metric learning for large margin nearest neighbor classification}},
journal = {Advances in Neural Information Processing Systems {\ldots}},
year = {2005}
}

@article{Weinberger:2009to,
author = {Weinberger, Kilian Q and Saul, Lawrence K},
title = {{Distance Metric Learning for Large Margin Nearest Neighbor Classification}},
journal = {The Journal of Machine Learning Research},
year = {2009},
volume = {10},
pages = {207--244},
month = dec
}

@article{Kopicki:2015ez,
author = {Kopicki, M and Detry, Renaud and Adjigble, M and Stolkin, R and Leonardis, A and Wyatt, J L},
title = {{One-shot learning and generation of dexterous grasps for novel objects}},
journal = {The International Journal of Robotics Research},
year = {2015},
month = sep
}

@inproceedings{Luo:vg,
author = {Luo, Guoliang and Bergstr{\"o}m, Niklas and Ek, Carl Henrik and Kragic, Danica},
title = {{Representing actions with kernels}},
booktitle = {2011 IEEE/RSJ International Conference on Intelligent Robots and Systems}
}

@article{Rue:2009uj,
author = {Rue, H and Martino, S and Chopin, N},
title = {{Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations - Rue - 2009 - Journal of the Royal Statistical Society: Series B (Statistical Methodology) - Wiley Online Library}},
journal = {Journal of the royal statistical {\ldots}},
year = {2009}
}

@article{Anderson:2003cm,
author = {Anderson, Michael L},
title = {{Embodied Cognition: A field guide.}},
journal = {Artif. Intell. ()},
year = {2003},
volume = {149},
number = {1},
pages = {91--130}
}

@article{Horaud:1998ka,
author = {Horaud, R and Dornaika, F and Espiau, B},
title = {{Visually guided object grasping}},
journal = {IEEE Transactions on Robotics and Automation},
year = {1998},
volume = {14},
number = {4},
pages = {525--532}
}

@article{Vahrenkamp:2012wr,
author = {Vahrenkamp, N and Asfour, Tamin and Metta, G},
title = {{Manipulability analysis}},
journal = {{\ldots} },
year = {2012}
}

@inproceedings{Athitsos:2003kc,
author = {Athitsos, V and Sclaroff, S},
title = {{Estimating 3D hand pose from a cluttered image}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2003 IEEE Conference on},
year = {2003},
annote = {<b>Second read.

Thoughts</b> 
- About his bounding box thing: is there a similar use for Dan's boyfriend's bounding box algorithm or did that have nothing to do with any of this? Should check this.   


<b>Review</b>
Building on previous work in: 3D Hand Pose Estimation by Finding Appearance-Based Matches in a Large Database of Training Views. 

The authors present hand pose estimation that is independent from viewpoint and handles clutter in what manner and to which extent is a bit unclear.

Basically they build on previous work using a big database of poses to match against a test image. They do a bit more with the Chamfer distance which measures the distance between binary images. It seems they find an approximation which is still robust but faster. They also develope a line segmentation approach that helps discriminate in early stages of the inference. 

First they use something called DCD to discriminate among a lot of pictures since the feature is really fast and then they press on with the Chamfer distance metric, line measure and histogram for fine tuning. 

The results they get are not super promising it seems. The accuracy seems to be around 60 percent or so. Unfortunatley their whole paper is a bit messy so it is really hard to understand exactly the tables 1-2 without a more thorough read. I haven't exactly understood the line features and the DCD. So I would need a third read. }
}

@article{Yang:2006wv,
author = {Yang, L and Jin, R},
title = {{Distance metric learning: A comprehensive survey}},
journal = {Michigan State Universiy},
year = {2006}
}

@article{Ahmed:2012vj,
author = {Ahmed, A and Ravi, S and Narayanamurthy, S},
title = {{FastEx: Hash Clustering with Exponential Families}},
journal = {Advances in Neural Information Processing Systems {\ldots}},
year = {2012}
}

@article{GuzmanRivera:2012tx,
author = {Guzman-Rivera, A and Batra, D and Kohli, Pushmeet},
title = {{Multiple Choice Learning: Learning to Produce Multiple Structured Outputs}},
journal = {Advances in Neural Information {\ldots}},
year = {2012}
}

@article{Marin:2011jh,
author = {Marin, Jean-Michel and Pudlo, Pierre and Robert, Christian P and Ryder, Robin J},
title = {{Approximate Bayesian computational methods}},
journal = {Statistics and Computing},
year = {2011},
volume = {22},
number = {6},
pages = {1167--1180},
month = oct
}

@webpage{Roweis:4C3ez6zT,
author = {Roweis, Sam},
title = {{Gaussian Identities}}
}

@article{Ohagan:1991tx,
author = {O'hagan, Anthony},
title = {{Bayes--Hermite quadrature}},
journal = {Journal of Statistical Planning and Inference},
year = {1991}
}

@proceedings{Chan:NIs0BNBa,
title = {{A 3D-Point-Cloud Feature for Human-Pose Estimation}}
}

@article{Buch:tz,
author = {Buch, A G and Kraft, D and Kamarainen, J K and Petersen, H G},
title = {{Pose Estimation using Local Structure-Specific Shape and Appearance Context}},
journal = {covil.sdu.dk
}
}

@article{Rudinac:2012kz,
author = {Rudinac, Maja and Kootstra, Gert and Kragic, Danica and Jonker, Pieter P},
title = {{Learning and recognition of objects inspired by early cognition.}},
journal = {IROS},
year = {2012},
pages = {4177--4184}
}

@article{Neto:2012wd,
author = {Neto, Sylvio Luiz Mantelli and de Aguiar, Daniel Besen and dos Santos, Bianca Sens and von Wangenheim, Aldo},
title = {{Multivariate Bayesian cognitive modeling for unsupervised quality control of baked pizzas}},
journal = {Machine Vision and Applications},
year = {2012},
volume = {23},
number = {3},
month = may
}

@article{McFee:2010va,
author = {McFee, B and Lanckriet, G},
title = {{Metric Learning to Rank}},
year = {2010}
}

@article{Kolter:kTpIXNN5,
author = {Kolter, Zico J and Jaakkola, Tommi S},
title = {{Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation}}
}

@inproceedings{Prats:2007bb,
author = {Prats, M and Sanz, P J and del Pobil, A P},
title = {{Task-Oriented Grasping using Hand Preshapes and Task Frames}},
booktitle = {2007 IEEE International Conference on Robotics and Automation},
year = {2007},
pages = {1794--1799}
}

@article{Salganicoff:1996fj,
author = {Salganicoff, Marcos and Ungar, Lyle H and Bajcsy, Ruzena},
title = {{Active Learning for Vision-Based Robot Grasping}},
journal = {Machine Learning},
year = {1996},
volume = {23},
number = {2/3},
pages = {251--278}
}

@inproceedings{Kappler:2010kd,
author = {Kappler, D and Chang, L and Przybylski, M and Pollard, N and Asfour, Tamin and Dillmann, R},
title = {{Representation of pre-grasp strategies for object manipulation}},
booktitle = {Humanoid Robots (Humanoids), 2010 10th IEEE-RAS International Conference on},
year = {2010},
pages = {617--624}
}

@article{Saut:2012vw,
author = {Saut, J P and Sidobre, D},
title = {{Efficient models for grasp planning with a multi-fingered hand}},
journal = {Robotics and Autonomous Systems},
year = {2012}
}

@inproceedings{Lawrence:2006ka,
author = {Lawrence, Neil D and Qui{\~n}onero-Candela, Joaquin},
title = {{Local distance preservation in the GP-LVM through back constraints}},
booktitle = {ICML '06: Proceedings of the 23rd international conference on Machine learning},
year = {2006},
publisher = { ACM},
month = jun
}

@article{Ek:2010tp,
author = {Ek, Carl Henrik and Song, Dan and Huebner, Kai},
title = {{Task Modeling in Imitation Learning using Latent Variable Models}},
journal = {{\ldots} (Humanoids)},
year = {2010}
}

@article{Shon:2005cy,
author = {Shon, Aaron P and Grochow, Keith and Rao, Rajesh P N},
title = {{Robotic imitation from human motion capture using Gaussian processes}},
journal = {{\ldots} (Humanoids)},
year = {2005},
pages = {129--134}
}

@article{Yoshikawa:1985bf,
author = {Yoshikawa, T},
title = {{Manipulability of Robotic Mechanisms}},
journal = {The International Journal of Robotics Research},
year = {1985},
volume = {4},
number = {2},
pages = {3--9},
month = jun
}

@article{Bromiely:-KqU1j8F,
author = {Bromiely, P.A.},
title = {{Products and Convolutions of Gaussian Distributions}},
year = {2003},
month = nov
}

@webpage{Ahrendt:v04-V9QB,
author = {Ahrendt, Peter},
title = {{The Multivariate Gaussian Probability Distribution}},
year = {2005},
month = jan
}

@article{Manton:2012vy,
author = {Manton, Jonathan H},
title = {{Differential Calculus, Tensor Products, and the Importance of Notation}},
journal = {arXiv.org},
year = {2012},
eprint = {1208.0197v1},
eprinttype = {arxiv},
eprintclass = {math.HO},
month = aug
}

@inproceedings{Prats:2007iv,
author = {Prats, Mario and Martinet, Philippe and del Pobil, Angel P and Lee, Sukhan},
title = {{VIsion force control in task-oriented grasping and manipulation}},
booktitle = {2007 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2007},
pages = {1320--1325},
publisher = {IEEE}
}

@inproceedings{Kitamura:1999dx,
author = {Kitamura, Tadashi},
title = {{Can a robot's adaptive behavior be animal-like without a learning algorithm?}},
booktitle = {Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on},
year = {1999},
pages = {1047--1051}
}

@article{LeCun:2012du,
author = {LeCun, Yann and Bottou, L{\'e}on and Orr, Genevieve B and M{\"u}ller, Klaus-Robert},
title = {{Efficient BackProp.}},
journal = {Neural Networks Tricks of the Trade (2nd ed.) 20129-48},
year = {2012}
}

@article{Stenger:2006dt,
author = {Stenger, Bj{\"o}rn and Thayananthan, Arasanathan and Torr, Philip H S and Cipolla, Roberto},
title = {{Model-based hand tracking using a hierarchical Bayesian filter}},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
year = {2006},
volume = {28},
number = {9},
pages = {1372--1384},
annote = {
Terms to lookup
Bayesian filtering, unscented Kalman filter (UKF)

Review
The authors present a hierachial tree based Bayesian filter. I think this built upon earlier research.}
}

@article{Oudeyer:2007ei,
author = {Oudeyer, P Y and Kaplan, F and Hafner, V V},
title = {{Intrinsic Motivation Systems for Autonomous Mental Development}},
journal = {Evolutionary Computation, IEEE Transactions on},
year = {2007},
volume = {11},
number = {2},
pages = {265--286}
}

@inproceedings{Osborne:2008wj,
author = {Osborne, M A and Roberts, Stephen J and Rogers, A and Ramchurn, S D and Jennings, N R},
title = {{Towards Real-Time Information Processing of Sensor Network Data Using Computationally Efficient Multi-output Gaussian Processes}},
booktitle = {IPSN '08: Proceedings of the 7th international conference on Information processing in sensor networks},
year = {2008},
publisher = { IEEE Computer Society},
month = apr
}

@article{Goodale:1991hc,
author = {Goodale, M A and Milner, A D and Jakobson, L S and Carey, D P},
title = {{A neurological dissociation between perceiving objects and grasping them.}},
journal = {Nature},
year = {1991},
volume = {349},
number = {6305},
pages = {154--156},
month = jan
}

@article{Teh:2006wl,
author = {Teh, Y W and {Jordan, Michael} and Beal, M J},
title = {{Hierarchical Dirichlet Processes}},
journal = {Journal of the American {\ldots}},
year = {2006}
}

@article{Osborne:2010vh,
author = {Osborne, M A},
title = {{Bayesian Gaussian processes for sequential prediction, optimisation and quadrature}},
year = {2010}
}

@inproceedings{Jaakkola:1996uk,
author = {Jaakkola, Tommi S and {Jordan, Michael}},
title = {{Computing upper and lower bounds on likelihoods in intractable networks}},
booktitle = {{\ldots} of the Twelfth international conference on {\ldots}},
year = {1996},
pages = {340--348},
publisher = {Morgan Kaufmann Publishers Inc.},
month = aug
}

@article{Lang:2010ur,
author = {Lang, T and Toussaint, M},
title = {{Planning with noisy probabilistic relational rules}},
journal = {Journal of Artificial Intelligence Research},
year = {2010}
}

@article{Fisher:1953un,
author = {Fisher, Ronald},
title = {{Dispersion on a Sphere}},
journal = {Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences},
year = {1953}
}

@inproceedings{Nicolescu:2001ew,
author = {Nicolescu, M N and Mataric, M J},
title = {{Experience-based representation construction: learning from human and robot teachers}},
booktitle = {Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference on},
year = {2001},
pages = {740--745}
}

@article{Boyle:2005uu,
author = {Boyle, P},
title = {{Dependent Gaussian Processes}},
journal = {Advances in Neural Information Processing Systems {\ldots}},
year = {2005}
}

@article{Nguyen:1992eq,
author = {Nguyen, T N and Stephanou, H E},
title = {{Topological reasoning about dextrous grasps}},
journal = {IBM Journal of Research and Development},
year = {1992},
volume = {36},
number = {3},
pages = {469--486}
}

@article{Jaakkola:1997vv,
author = {Jaakkola, Tommi S and {Jordan, Michael}},
title = {{A variational approach to Bayesian logistic regression models and their extensions}},
year = {1997}
}

@article{Hoiem:2005kb,
author = {Hoiem, Derek and Efros, Alexei A and Hebert, Martial},
title = {{Geometric Context from a Single Image.}},
journal = {ICCV},
year = {2005},
pages = {654--661}
}

@article{Chemero:2003da,
author = {Chemero, Anthony},
title = {{An Outline of a Theory of Affordances}},
journal = {Ecological Psychology},
year = {2003},
volume = {15},
number = {2},
pages = {181--195},
month = apr
}

@inproceedings{Nguyen:1990dx,
author = {Nguyen, T N and Stephanou, H E},
title = {{Topological reasoning about dextrous manipulation}},
booktitle = {Decision and Control, 1990., Proceedings of the 29th IEEE Conference on},
year = {1990},
pages = {2214--2219}
}

@inproceedings{Shilane:2004hh,
author = {Shilane, P and Min, P and Kazhdan, M and Funkhouser, T},
title = {{The Princeton Shape Benchmark}},
booktitle = {Shape Modeling Applications, 2004. Proceedings},
year = {2004},
pages = {167--178}
}

@article{Vogiatzis:2008ej,
author = {Vogiatzis, George and Torr, Philip H S and Seitz, Steven M and Cipolla, Roberto},
title = {{Reconstructing relief surfaces}},
journal = {Image and Vision Computing},
year = {2008},
volume = {26},
number = {3},
pages = {397--404},
month = mar
}

@article{Li:2012vv,
author = {Li, Q and Haschke, R and Ritter, H and Bolder, B},
title = {{Towards Unknown Objects Manipulation⋆}},
journal = {Robot Control},
year = {2012}
}

@article{Karpathy:wu,
author = {Karpathy, A and Miller, S and Fei-Fei, L},
title = {{Object Discovery in 3D scenes via Shape Analysis}},
journal = {www-cs.stanford.edu
}
}

@article{Ek:2010wk,
author = {Ek, Carl Henrik and Song, Dan and Huebner, Kai and Kragic, Danica},
title = {{Exploring affordances in robot grasping through latent structure representation}},
journal = {Vision for Cognitive Tasks},
year = {2010}
}

@book{Magnus:1999vh,
author = {Magnus, Jan and Neudecker, Heinz},
title = {{Matrix Differential Calculus with Applications in Statistics and Econometrics}},
publisher = {Wiley},
year = {1999},
edition = {2},
month = mar
}

@article{Shon:2006wr,
author = {Shon, A and Grochow, K and Hertzmann, A},
title = {{Learning shared latent structure for image synthesis and robotic imitation}},
journal = {Advances in Neural Information Processing Systems {\ldots}},
year = {2006}
}

@article{ORourke:epii_GiV,
author = {O'Rourke, Keith},
title = {{Drawing Out Model Based Inference: Simulation based
plotting methods to discern and display replication from
di{\S}erent sources.}}
}

@inproceedings{Hsiao:2010kw,
author = {Hsiao, K and Chitta, S and Ciocarlie, Matei T and Jones, E G},
title = {{Contact-reactive grasping of objects with partial shape information}},
booktitle = {2010 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2010},
pages = {1228--1235}
}

@article{Arena:2009dl,
author = {Arena, P and Patane, L},
title = {{Simple sensors provide inputs for cognitive robots}},
journal = {IEEE Instrumentation {\&} Measurement Magazine},
year = {2009},
volume = {12},
number = {3},
pages = {13--20}
}

@inproceedings{Fitzpatrick:2003ho,
author = {Fitzpatrick, P and Metta, G and Natale, L and Rao, S and Sandini, G},
title = {{Learning about objects through action - initial steps towards artificial cognition}},
booktitle = {2003 IEEE International Conference on Robotics and Automation},
year = {2003},
pages = {3140--3145}
}

@article{Jakel:2012gi,
author = {J{\"a}kel, Rainer and Schmidt-Rohr, Sven R and R{\"u}hl, Steffen W and Kasper, Alexander and Xue, Zhixing and Dillmann, R{\"u}diger},
title = {{Learning of Planning Models for Dexterous Manipulation Based on Human Demonstrations}},
journal = {International Journal of Social Robotics},
year = {2012},
volume = {4},
number = {4},
pages = {437--448},
month = jun
}

@article{Hsu:2012uq,
author = {Hsu, Daniel and Kakade, Sham M and Zhang, Tong},
title = {{A spectral algorithm for learning Hidden Markov Models}},
journal = {Journal of Computer and System Sciences},
year = {2012},
volume = {78},
number = {5},
month = sep
}

@article{Ying:2007go,
author = {Ying, Li and Fu, Jiaxin L and Pollard, Nancy S},
title = {{Data-Driven Grasp Synthesis Using Shape Matching and Task-Based Pruning}},
journal = {Visualization and Computer Graphics, IEEE Transactions on},
year = {2007},
volume = {13},
number = {4},
pages = {732--747}
}

@article{Salzmann:2010vh,
author = {Salzmann, Mathieu and Ek, Carl Henrik and Urtasun, Raquel},
title = {{Factorized orthogonal latent spaces}},
journal = {{\ldots} Conference on Artificial {\ldots}},
year = {2010}
}

@article{Jaakkola:2000wr,
author = {Jaakkola, Tommi S and {Jordan, Michael}},
title = {{Bayesian parameter estimation via variational methods - Springer}},
journal = {Statistics and Computing},
year = {2000}
}

@article{Rasmussen:1999wi,
author = {Rasmussen, C E},
title = {{The infinite Gaussian mixture model.}},
journal = {NIPS},
year = {1999}
}

@article{Hjelm:2014uc,
author = {Hjelm, Martin and Detry, Renaud and Ek, Carl Henrik and Kragic, Danica},
title = {{Representations for Cross-task, Cross-object Grasp Transfer}},
journal = {IEEE International Conference on {\ldots}},
year = {2014}
}

@article{Chandrasekaran:2013vt,
author = {Chandrasekaran, Venkat and {Jordan, Michael}},
title = {{Computational and statistical tradeoffs via convex relaxation}},
journal = {Proceedings of the {\ldots}},
year = {2013}
}

@article{Bitzer:2008kw,
author = {Bitzer, Sebastian and Havoutis, Ioannis and Vijayakumar, Sethu},
title = {{Synthesising Novel Movements through Latent Space Modulation of Scalable Control Policies}},
journal = {From Animals to Animats 10},
year = {2008},
volume = {5040},
number = {Chapter 20},
pages = {199--209}
}

@article{Ericsson:2007en,
author = {Ericsson, K Anders and Ward, Paul},
title = {{Capturing the Naturally Occurring Superior Performance of Experts in the Laboratory: Toward a Science of Expert and Exceptional Performance}},
journal = {Current Directions in Psychological Science},
year = {2007},
volume = {16},
number = {6},
pages = {346--350},
month = dec
}

@article{Montesano:2012tr,
author = {Montesano, L and Lopes, M},
title = {{Active learning of visual descriptors for grasping using non-parametric smoothed beta distributions}},
journal = {Robotics and Autonomous Systems},
year = {2012}
}

@inproceedings{Kehoe:2013jv,
author = {Kehoe, B and Matsukawa, A and Candido, S and Kuffner, J and Goldberg, K},
title = {{Cloud-based robot grasping with the google object recognition engine}},
booktitle = {Robotics and Automation (ICRA), 2013 IEEE International Conference on},
year = {2013},
pages = {4263--4270}
}

@article{Verma:2006uh,
author = {Verma, D and Rao, R},
title = {{Goal-based imitation as probabilistic inference over graphical models}},
journal = {Advances in Neural Information Processing Systems {\ldots}},
year = {2006}
}

@article{Khoshelham:2012jl,
author = {Khoshelham, Kourosh and Elberink, Sander Oude},
title = {{Accuracy and resolution of Kinect depth data for indoor mapping applications.}},
journal = {Sensors (Basel, Switzerland)},
year = {2012},
volume = {12},
number = {2},
pages = {1437--1454}
}

@article{Zhang:2011up,
author = {Zhang, L E and Ciocarlie, Matei T and Hsiao, K},
title = {{Grasp evaluation with graspable feature matching}},
journal = {RSS Workshop on Mobile {\ldots}},
year = {2011},
annote = {<b>Summary:</b>

Transforms a point cloud of an object into a voxel grid.    }
}

@inproceedings{Liu:2014ij,
author = {Liu, Jia and Feng, Fangxiaoyu and Nakamura, Yuzuko C and Pollard, Nancy S},
title = {{A taxonomy of everyday grasps in action}},
booktitle = {Humanoid Robots (Humanoids), 2014 14th IEEE-RAS International Conference on},
year = {2014},
pages = {573--580}
}

@article{Gibson:1988wp,
author = {Gibson, E J},
title = {{Exploratory behavior in the development of perceiving, acting, and the acquiring of knowledge}},
journal = {Annual review of psychology},
year = {1988}
}

@article{Kazemi:6ehrwE8b,
author = {Kazemi, Vahid and Sullivan, Josephine},
title = {{Face Alignment with Part-Based Modeling}}
}

@article{Kadri:-bUcItGO,
author = {Kadri, Hachem},
title = {{A Generalized Kernel Approach to Structured Output Learning}}
}

@article{Andrieu:2003kt,
author = {Andrieu, Christophe and de Freitas, Nando and Doucet, Arnaud and {Jordan, Michael}},
title = {{An Introduction to MCMC for Machine Learning}},
journal = {Machine Learning},
year = {2003},
volume = {50},
number = {1/2},
pages = {5--43}
}

@article{Bertenthal:1996cz,
author = {Bertenthal, Bennett I},
title = {{Origins and Early Development of Perception, Action, and Representation}},
journal = {Annual review of psychology},
year = {1996},
volume = {47},
number = {1},
pages = {431--459},
month = feb
}

@article{Venkatasubramanian:2013ww,
author = {Venkatasubramanian, S},
title = {{Moving heaven and earth}},
journal = {ACM SIGACT News},
year = {2013}
}

@inproceedings{Song:2011hk,
author = {Song, Dan and Ek, Carl Henrik and Huebner, Kai and Kragic, Danica},
title = {{Embodiment-specific representation of robot grasping using graphical models and latent-space discretization}},
booktitle = {2011 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2011},
pages = {980--986}
}

@article{Scholkopft:1999tz,
author = {Scholkopft, B and Mullert, K R},
title = {{Fisher discriminant analysis with kernels}},
journal = {Neural networks for signal {\ldots}},
year = {1999}
}

@inproceedings{Illing:2014fg,
author = {Illing, B and Asfour, Tamin and Pollard, N S},
title = {{Changing pre-grasp strategies with increasing object location uncertainty}},
booktitle = {Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on},
year = {2014},
pages = {2468--2475}
}

@book{Barrett:1987ti,
author = {Barrett, Richard and Berry, Michael and Chan, Tony F and Demmel, James and Donato, June and Dongarra, Jack and Eijkhout, Victor and Pozo, Roldan and Romine, Charles and van der Vorst, Henk},
title = {{Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods (Miscellaneous Titles in Applied Mathematics Series No 43)}},
publisher = {Society for Industrial and Applied Mathematics},
year = {1987},
edition = {2},
month = jan
}

@article{Calinon:2007ef,
author = {Calinon, Sylvain and Guenter, Florent and Billard, Aude},
title = {{On Learning, Representing, and Generalizing a Task in a Humanoid Robot}},
journal = {IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics)},
year = {2007},
volume = {37},
number = {2},
pages = {286--298},
month = apr
}

@article{Faillenot:1997fr,
author = {Faillenot, I},
title = {{Visual pathways for object-oriented action and object recognition: functional anatomy with PET}},
journal = {Cerebral Cortex},
year = {1997},
volume = {7},
number = {1},
pages = {77--85},
month = jan
}

@inproceedings{Burenius:2011fw,
author = {Burenius, Magnus and Sullivan, Josephine and Carlsson, Stefan},
title = {{Motion capture from dynamic orthographic cameras}},
booktitle = {2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)},
year = {2011},
pages = {1634--1641},
publisher = {IEEE}
}

@article{Culham:2003eo,
author = {Culham, Jody C and Danckert, Stacey L and Souza, Joseph F X De and Gati, Joseph S and Menon, Ravi S and Goodale, Melvyn A},
title = {{Visually guided grasping produces fMRI activation in dorsal but not ventral stream brain areas}},
journal = {Experimental Brain Research},
year = {2003},
volume = {153},
number = {2},
pages = {180--189},
month = nov
}

@inproceedings{LingqiaoLiu:2012en,
author = {Lingqiao Liu and Lei Wang},
title = {{What has my classifier learned? Visualizing the classification rules of bag-of-feature model by support region detection}},
booktitle = {2012 IEEE Conference on Computer Vision and Pattern Recognition},
year = {2012},
pages = {3586--3593},
publisher = {IEEE}
}

@inproceedings{Lin:2013hp,
author = {Lin, Yun and Sun, Yu},
title = {{Grasp mapping using locality preserving projections and kNN regression}},
booktitle = {Robotics and Automation (ICRA), 2013 IEEE International Conference on},
year = {2013},
pages = {1076--1081}
}

@inproceedings{Stenger:2001gg,
author = {Stenger, Bj{\"o}rn and Mendonca, P R S and Cipolla, Roberto},
title = {{Model-based 3D tracking of an articulated hand}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2001 IEEE Conference on},
year = {2001},
annote = {<b>Secon Read.

Terms to loookup</b> 
Unscented Klamn filter, Hogg features, Second degree implicit surface

<b>Thoughts</b>: 
Basically a matching problem done via Kalman filtering. Novelty is perhaps the 3D model and using that for generating silohouetts. Otherwise the paper is pretty unsexy and badly written. Evaluation / results is also pretty nonexistant which seems to imply that method doesn't work fantastically...

<b>Review:</b>
Quite unclear what this paper does in detail from reading the introduction and conclusion sections. After reading the entire paper things are a bit clearer but this paper is lacking in the explanation of how the actually tracking is done.

This is a short summary of how I think this is done: They build a 3D model of a real hand, composed of 27 different objects. Using the hand model they can match the edges/silohouetts of the model hand against the edges/silhouettes in the image. The matching of the two is made by an Unscented Kalman Filter. How that is done is a bit unclear since my knowledge about Kalman filters is almost zero.}
}

@article{Sudderth:2006wn,
author = {Sudderth, Erik B},
title = {{Graphical models for visual object recognition and tracking}},
year = {2006}
}

@article{Faria:2014ug,
author = {Faria, D R and Trindade, P and Lobo, J and Dias, J},
title = {{Knowledge-based reasoning from human grasp demonstrations for robot grasp synthesis}},
journal = {Robotics and Autonomous Systems},
year = {2014}
}

@booklet{Rusu:2009wu,
title = {{Semantic 3D Object Maps for Everyday Manipulation in Human Living Environments}},
author = {Rusu, Radu Bogdan},
year = {2009}
}

@article{springerlink:10.1007/978-3-642-15567-3_17,
author = {Hedau, Varsha and Hoiem, Derek and Forsyth, David},
title = {{Thinking Inside the Box: Using Appearance Models and Context Based on Room Geometry}},
year = {2010},
volume = {6316},
number = {Chapter 17},
pages = {224--237}
}

@article{Bowers:2003cy,
author = {Bowers, D L and Lumia, R},
title = {{Manipulation of unmodeled objects using intelligent grasping schemes}},
journal = {Fuzzy Systems, IEEE Transactions on},
year = {2003},
volume = {11},
number = {3},
pages = {320--330}
}

@article{Schaal:2004dq,
author = {Schaal, Stefan and Sternad, Dagmar and Osu, Rieko and Kawato, Mitsuo},
title = {{Rhythmic arm movement is not discrete}},
journal = {Nature Neuroscience},
year = {2004},
volume = {7},
number = {10},
pages = {1136--1143},
month = sep
}

@article{Saxena:2008wt,
author = {Saxena, A and Wong, LLS and Ng, Andrew Y.},
title = {{Learning Grasp Strategies with Partial Shape Information}},
journal = {AAAI},
year = {2008}
}

@article{Chib:1995ud,
author = {Chib, Siddhartha and Greeenberg, Edward},
title = {{Understanding the Metropolis-Hastings Algorithm}},
journal = {American Statistician},
year = {1995},
volume = {49},
number = {4},
pages = {327--335}
}

@inproceedings{Chao:2011id,
author = {Chao, Crystal and Cakmak, Maya and Thomaz, Andrea L},
title = {{Towards grounding concepts for transfer in goal learning from demonstration}},
booktitle = {2011 IEEE International Conference on Development and Learning},
year = {2011},
pages = {1--6}
}

@article{Hartson:2003kf,
author = {Hartson, H Rex},
title = {{Cognitive, physical, sensory, and functional affordances in interaction design.}},
journal = {Behaviour {\&} IT ()},
year = {2003},
volume = {22},
number = {5},
pages = {315--338}
}

@article{Miller:2004kw,
author = {Miller, A T and Allen, P K},
title = {{GraspIt!}},
journal = {IEEE Robotics {\&} Automation Magazine},
year = {2004},
volume = {11},
number = {4},
pages = {110--122},
month = dec
}

@inproceedings{Hindi:2004tw,
author = {Hindi, H},
title = {{A tutorial on convex optimization}},
booktitle = {American Control Conference, 2004. Proceedings of the 2004},
year = {2004},
pages = {3252--3265}
}

@inproceedings{Rusu:2010db,
author = {Rusu, R B and Bradski, G and Thibaux, R and Hsu, J},
title = {{Fast 3D recognition and pose using the Viewpoint Feature Histogram}},
booktitle = {2010 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2010},
pages = {2155--2162}
}

@article{Hinterstoisser:2012fo,
author = {Hinterstoisser, S and Cagniart, C and Ilic, S and Sturm, P and Navab, N and Fua, P and Lepetit, V},
title = {{Gradient Response Maps for Real-Time Detection of Textureless Objects}},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2012},
volume = {34},
number = {5},
pages = {876--888},
month = may
}

@inproceedings{Bitzer:2010cy,
author = {Bitzer, Sebastian and Howard, M and Vijayakumar, Sethu},
title = {{Using dimensionality reduction to exploit constraints in reinforcement learning}},
booktitle = {2010 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2010},
pages = {3219--3225}
}

@article{Coradeschi:2013jr,
author = {Coradeschi, Silvia and Loutfi, Amy and Wrede, Britta},
title = {{A Short Review of Symbol Grounding in Robotic and Intelligent Systems.}},
journal = {KI},
year = {2013},
volume = {27},
number = {2},
pages = {129--136}
}

@article{Faria:2012dp,
author = {Faria, Diego R and Martins, Ricardo and Lobo, Jorge and Dias, Jorge},
title = {{Extracting data from human manipulation of objects towards improving autonomous robotic grasping}},
journal = {Robotics and Autonomous Systems},
year = {2012},
volume = {60},
number = {3},
pages = {396--410},
month = mar
}

@article{Ghahramani:2012dt,
author = {Ghahramani, Zoubin},
title = {{Bayesian non-parametrics and the probabilistic approach to modelling}},
journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
year = {2012},
volume = {371},
number = {1984},
pages = {20110553--20110553},
month = dec
}

@article{Stenger:2004hl,
author = {Stenger, Bj{\"o}rn and Thayananthan, Arasanathan and Torr, Philip H S and Cipolla, Roberto},
title = {{Hand Pose Estimation Using Hierarchical Detection}},
journal = {Computer Vision in Human {\ldots}},
year = {2004},
volume = {3058},
number = {Chapter 11},
pages = {105--116},
annote = {<b>Second read.

Thoughts</b>
I should do all the labs in Josephine's image recognition course and the exam. 

<b>Review</b>
This paper tests different features and different template methods for a cascade classifier on hand pose recognition. The two features evaluated are edge and color.

The <b>classifier</b> is some sort of tree-based cascade classifier. Basically its cascade evaluation search over a coarse grid and then on a further refined grid. The method is not explained very good but seems to be to create some sort of binary grid. The authors refer to a paper of theirs on filtering using a tree-based estimator. 

The <b>edge feature</b> is evaluated using different kinds of template methods to see which one is more robust to differences in the template vs the image the template is appplied to. To improve robustness one can either blur the edge image or template before correlating or use the Chamfer or Hausdorff distance measure. This paragraph is a bit unclear if I remember it correctly the Chamfer distance is a blurring. The authors present 3 different template approaches for the edge feature. Centre template is basically a single shape template using both the Chamfer and Hausdorff distance. <b>Marginalized template</b> is a template which is more attuned to a specific region in the template and setting the model parameters based upon on this region and not the whole template. <b>Linear classifier learnt from image data</b> basically learning the template by supervised learning using a perceptron 1000 positive and 4000 negative examples.

The <b>skin color feature</b> is a bit vaguely presented refering to Stenger's PhD thesis. My notion of how this feature is used with templates is the following: model the skincolor as a Gaussian in rg-space and the background as a uniform distribution, extract a log-likelihood map of the skincolor and a map for the background color. Both features can be written as a cost function representing the full log-likelihood or deducted likelihood which apparently is equivalent to matching a template. No thorough motivation is given though.

 

 

}
}

@inproceedings{Hedau:2009gr,
author = {Hedau, Varsha and Hoiem, Derek and Forsyth, David},
title = {{Recovering the Spatial Layout of Cluttered Rooms}},
booktitle = {2009 IEEE International Conference on Computer Vision},
year = {2009},
pages = {1849--1856},
publisher = {IEEE}
}

@article{Kuniyoshi:1994id,
author = {Kuniyoshi, Y and Inaba, M and Inoue, H},
title = {{Learning by watching: extracting reusable task knowledge from visual observation of human performance}},
journal = {Robotics and Automation, IEEE Transactions on},
year = {1994},
volume = {10},
number = {6},
pages = {799--822},
annote = {Some good formulations concerning how to think. Otherwise time has made this paper old.
}
}

@article{Hensman:kFi_-hfa,
author = {Hensman, James and Lawrence, Neil D},
title = {{Gaussian Processes for Big Data through Stochastic Variational Inference}}
}

@inproceedings{Bouchard:2005ew,
author = {Bouchard, G and Triggs, B},
title = {{Hierarchical part-based visual object categorization}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2005 IEEE Conference on},
year = {2005},
pages = {710--715}
}

@inproceedings{RedondoCabrera:2012kh,
author = {Redondo-Cabrera, C and Lopez-Sastre, R J and Acevedo-Rodriguez, J and Maldonado-Bascon, S},
title = {{SURFing the point clouds: Selective 3D spatial pyramids for category-level object recognition}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on},
year = {2012},
pages = {3458--3465}
}

@article{Herskovits:1992ur,
author = {Herskovits, E},
title = {{A Bayesian method for the induction of probabilistic networks from data}},
journal = {Machine Learning},
year = {1992}
}

@inproceedings{Stansfield:1990cc,
author = {Stansfield, S A},
title = {{Knowledge-based robotic grasping}},
booktitle = {1990 IEEE International Conference on Robotics and Automation},
year = {1990},
pages = {1270--1275}
}

@article{Fackler:2005wu,
author = {Fackler, PL},
title = {{Notes on matrix calculus}},
journal = {North Carolina State University},
year = {2005}
}

@article{Grave:2013iz,
author = {Gr{\"a}ve, Kathrin and Behnke, Sven},
title = {{Learning sequential tasks interactively from demonstrations and own experience.}},
journal = {IROS},
year = {2013},
pages = {3237--3243}
}

@article{Skurichina:2002ge,
author = {Skurichina, Marina and Duin, Robert P W},
title = {{Bagging, Boosting and the Random Subspace Method for Linear Classifiers.}},
journal = {Pattern Anal. Appl. ()},
year = {2002},
volume = {5},
number = {2},
pages = {121--135}
}

@article{Johnson:1999cj,
author = {Johnson, A E and Hebert, M},
title = {{Using spin images for efficient object recognition in cluttered 3D scenes}},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {1999},
volume = {21},
number = {5},
pages = {433--449},
month = may
}

@article{Gentsch:2016ca,
author = {Gentsch, Antje and Weber, Arne and Synofzik, Matthis and Vosgerau, Gottfried and Sch{\"u}tz-Bosbach, Simone},
title = {{Towards a common framework of grounded action cognition: Relating motor control, perception and cognition.}},
journal = {Cognition},
year = {2016},
volume = {146},
pages = {81--89},
month = jan
}

@article{Lawrence:2005vz,
author = {Lawrence, Neil D and Seeger, Mattias},
title = {{The informative vector machine: A practical probabilistic alternative to the support vector machine}},
journal = {Dept Computer Science},
year = {2005}
}

@article{Minka:2003vv,
author = {Minka, Thomas P},
title = {{The 'summation hack'as an outlier model}},
journal = {Tutorial note},
year = {2003}
}

@inproceedings{Knopp:2010uo,
author = {Knopp, Jan and Prasad, Mukta and Willems, Geert and Timofte, Radu and Van Gool, Luc},
title = {{Hough transform and 3D SURF for robust three dimensional classification}},
booktitle = {ECCV'10: Proceedings of the 11th European conference on Computer vision: Part VI},
year = {2010},
publisher = { Springer-Verlag},
month = sep
}

@article{Baltzakis:2001wo,
author = {Baltzakis, HG and Trahanias, PE},
title = {{The VPLF method for vanishing point computation}},
journal = {Image and Vision Computing},
year = {2001},
volume = {19},
number = {6},
pages = {393--400}
}

@article{Griffiths:2011to,
author = {Griffiths, Thomas L and Ghahramani, Zoubin},
title = {{The Indian Buffet Process: An Introduction and Review}},
journal = {The Journal of Machine Learning Research},
year = {2011},
volume = {12},
month = feb
}

@inproceedings{Drost:2010kn,
author = {Drost, B and Ulrich, Markus and Navab, N and Ilic, S},
title = {{Model globally, match locally: Efficient and robust 3D object recognition}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on},
year = {2010},
pages = {998--1005}
}

@article{Lopes:2005eh,
author = {Lopes, M and Santos-Victor, Jos{\'e}},
title = {{Visual learning by imitation with motor representations}},
journal = {Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on},
year = {2005},
volume = {35},
number = {3},
pages = {438--449}
}

@article{Desautels:2012ua,
author = {Desautels, Thomas and Krause, Andreas and Burdick, Joel},
title = {{Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization}},
journal = {arXiv.org},
year = {2012},
month = jun
}

@inproceedings{Guyon:dj,
author = {Guyon, I and Alamdari, A R S A and Dror, G and Buhmann, J M Neural Networks 2006 IJCNN '06 International Joint Conference on},
title = {{Performance Prediction Challenge}},
booktitle = {Neural Networks, 2006. IJCNN '06. International Joint Conference on}
}

@inproceedings{Miller:1999dn,
author = {Miller, A T and Allen, P K},
title = {{Examples of 3D grasp quality computations}},
booktitle = {1999 IEEE International Conference on Robotics and Automation},
year = {1999},
pages = {1240--1246}
}

@article{Castiello:2005gq,
author = {Castiello, Umberto},
title = {{The neuroscience of grasping}},
journal = {Nature Reviews Neuroscience},
year = {2005},
volume = {6},
number = {9},
pages = {726--736},
month = aug
}

@article{Felsberg:2009fn,
author = {Felsberg, Michael and Wiklund, Johan and Granlund, G{\"o}sta H},
title = {{Exploratory learning structures in artificial cognitive systems.}},
journal = {Image and Vision Computing},
year = {2009},
volume = {27},
number = {11},
pages = {1671--1687}
}

@article{Neal:1993vg,
author = {Neal, R M},
title = {{Probabilistic inference using Markov chain Monte Carlo methods}},
year = {1993}
}

@article{Bishop:1998wp,
author = {Bishop, Christopher M and Svens{\'e}n, M and Williams, Christopher K I},
title = {{GTM: The generative topographic mapping}},
journal = {Neural Computation},
year = {1998},
annote = {<b>Summary / Review</b>
Introduces the GTM. The GTM is a latent variable model where the latent variables are nodes on a grid. The prior on the latent variables are a mixture of Dirac delta functions. The latent variables are mapped via a matrix W to the data space Y. By using a nonlinear transform of the X values the mapping is written as y = Wf(x).  The mapping parameters / weights, W, plus the rest of parameters are found via maximizing the log likelihood for the data, Y. The authors don't use nonlinear optimization techniques such as Newtonian or conjugate gradients etc. but instead formulates the maximization as a EM problem via the realization that the model is mixture model.

Compared to SOM it seems to have some nice qualities such as a probability distribution over the latent space and convergence guarantees etc. However it is slower than the optimized SOM that takes almos half the time to complete in one of the experiments. This is to be expected since it is a severely ill-conditioned problem.
   }
}

@article{Teh:2010wf,
author = {Teh, Y W},
title = {{Dirichlet Process}},
journal = {Encyclopedia of machine learning},
year = {2010}
}

@inproceedings{Nowozin:2011ji,
author = {Nowozin, Sebastian and Rother, Carsten and Bagon, Shai and Sharp, Toby and Yao, Bangpeng and Kohli, Pushmeet},
title = {{Decision tree fields}},
booktitle = {Computer Vision (ICCV), 2011 IEEE International Conference on},
year = {2011},
pages = {1668--1675}
}

@article{Minka:2001we,
author = {Minka, Thomas P},
title = {{Expectation propagation for approximate Bayesian inference}},
journal = {Uncertainty in Artificial Intelligence},
year = {2001}
}

@article{Lawrence:Lz469Arm,
author = {Lawrence, Neil D},
title = {{Large scale learning with the Gaussian process latent variable model. Technical Report CS-06-05}},
annote = {

The main differences between the covariances involve the approximation of the covariance matrix for the training conditional p(f_u|u) i.e. the probability of the function values of the inducing points conditioned on the function values.

- The DTCVAR approximation have a zero covariance training conditional i.e. P(f|f_u) = P( K_nm * K_mm * u, 0 ). This implies no correlations between any points in the function values meaning that they are all arbitrary given the inducing points function values.

- FITC AND PITC on the other hand involve    }
}

@article{Singh:2008ii,
author = {Singh, Gurjeet and Memoli, Facundo and Ishkhanov, Tigran and Sapiro, Guillermo and Carlsson, Gunnar and Ringach, Dario L},
title = {{Topological analysis of population activity in visual cortex.}},
journal = {Journal of vision},
year = {2008},
volume = {8},
number = {8},
pages = {11.1--18}
}

@article{Marton:2011co,
author = {Marton, Z C and Pangercic, D and Blodow, N and Beetz, M},
title = {{Combined 2D-3D categorization and classification for multimodal perception systems}},
journal = {The International Journal of Robotics Research},
year = {2011},
volume = {30},
number = {11},
pages = {1378--1402},
month = oct
}

@book{Boyd:2004uz,
author = {Boyd, Stephen and Vandenberghe, Lieven},
title = {{Convex Optimization}},
publisher = {Cambridge University Press},
year = {2004},
month = mar
}

@article{Grauman:2007uc,
author = {Grauman, Kristen and Darrell, Trevor J},
title = {{The Pyramid Match Kernel: Efficient Learning with Sets of Features}},
journal = {The Journal of Machine Learning Research},
year = {2007},
volume = {8},
pages = {725--760},
month = may
}

@article{Weston:2012wz,
author = {Weston, Jason and Wang, Chong and Weiss, Ron and Berenzweig, Adam},
title = {{Latent Collaborative Retrieval}},
journal = {arXiv.org},
year = {2012},
eprint = {1206.4603v1},
eprinttype = {arxiv},
eprintclass = {cs.IR},
month = jun,
annote = {ICML2012

<b>Review
</b>Introduces the concept of <b>collaborative retrieval</b>. It means augmenting a item query task with user information of how the user ranks and sees items in its universe. Basically what it means is that they take into account the users preferences when they make a query. What they also do is to take queries into account when training the model i.e. the training data is augmented with queries.



 }
}

@article{Blei:2003tn,
author = {Blei, David M. and Ng, Andrew Y. and {Jordan, Michael}},
title = {{Latent dirichlet allocation}},
journal = {The Journal of Machine Learning Research},
year = {2003},
volume = {3},
pages = {993--1022},
month = mar
}

@article{Anand:2011tv,
author = {Anand, Abhishek and Koppula, Hema Swetha and Joachims, Thorsten and Saxena, Ashutosh},
title = {{Contextually Guided Semantic Labeling and Search for 3D Point Clouds}},
journal = {arXiv.org},
year = {2011},
eprint = {1111.5358v3},
eprinttype = {arxiv},
eprintclass = {cs.RO},
month = nov,
annote = {arXiv admin note: substantial text overlap with arXiv:1106.5551}
}

@article{Mian:2006bz,
author = {Mian, Ajmal S and Bennamoun, Mohammed and Owens, Robyn},
title = {{Three-dimensional model-based object recognition and segmentation in cluttered scenes.}},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2006},
volume = {28},
number = {10},
pages = {1584--1601},
month = oct
}

@inproceedings{Lazebnik:2006do,
author = {Lazebnik, S and Schmid, C and Ponce, J},
title = {{Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2006 IEEE Conference on},
year = {2006},
pages = {2169--2178}
}

@article{Nicolau:2011wz,
author = {Nicolau, Monica and Levine, Arnold J and Carlsson, Gunnar},
title = {{Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival}},
journal = {Proceedings of the {\ldots}},
year = {2011}
}

@inproceedings{Granlund:1999we,
author = {Granlund, G},
title = {{Does vision inevitably have to be active?}},
booktitle = {Proceedings of the Scandinavian Conference on {\ldots}},
year = {1999}
}

@article{Acklam:2000wb,
author = {Acklam, PJ},
title = {{MATLAB array manipulation tips and tricks}},
journal = {Statistics Division},
year = {2000}
}

@article{Saxena:2008wn,
author = {Saxena, Ashutosh and Driemeyer, Justin and Ng, Andrew Y.},
title = {{Robotic Grasping of Novel Objects using Vision}},
journal = {{\ldots} International Journal of Robotics {\ldots}},
year = {2008},
annote = {Review:

Using 2D pictures and optimal grasping points on the object in the picture they train an image classifier on multiple viewpoints. To grasp an object they identify in a 2D image possible points for grasping by using the classifier.  They correlate the hypothesised points to a 3D point cloud and generate a grasp. }
}

@article{Day:1998gq,
author = {Day, Robert A},
title = {{How to Write and Publish Scientific Papers}},
journal = {Mem{\'o}rias do Instituto Oswaldo Cruz},
year = {1998},
volume = {93},
number = {3},
pages = {000--000}
}

@proceedings{Kalmbach:YoRPvECr,
title = {{Unsupervised Environment Recognition and Modeling using Sound Sensing}}
}

@inproceedings{Rusu:2009hf,
author = {Rusu, Radu Bogdan and Blodow, Nico and Beetz, Michael},
title = {{Fast Point Feature Histograms (FPFH) for 3D registration}},
booktitle = {2009 IEEE International Conference on Robotics and Automation},
year = {2009},
pages = {3212--3217},
publisher = {IEEE}
}

@article{Shivaswamy:2012ty,
author = {Shivaswamy, Pannaga and Joachims, Thorsten},
title = {{Online Structured Prediction via Coactive Learning}},
journal = {arXiv.org},
year = {2012},
eprint = {1205.4213v2},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = may
}

@article{Talwalkar:2010vn,
author = {Talwalkar, Ameet and Rostamizadeh, Afshin},
title = {{Matrix Coherence and the Nystrom Method}},
journal = {arXiv.org},
year = {2010},
month = apr
}

@article{Davis:2012td,
author = {Davis, M and Davis, K J and Dunagan, M},
title = {{Scientific Papers and Presentations - Martha Davis, Kaaron Joann Davis, Marion M. Dunagan - Google Books}},
year = {2012}
}

@article{Cheng:2001vf,
author = {Cheng, S H and Higham, N J and Kenney, C S and Laub, Alan J},
title = {{Approximating the logarithm of a matrix to specified accuracy}},
journal = {SIAM Journal on Matrix {\ldots}},
year = {2001}
}

@inproceedings{Rusu:2009bo,
author = {Rusu, Radu Bogdan and Holzbach, Andreas and Blodow, Nico and Beetz, Michael},
title = {{Fast geometric point labeling using conditional random fields}},
booktitle = {2009 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2009},
pages = {7--12},
publisher = {IEEE}
}

@article{IBMRD:2000tg,
author = {IBMRD, International Business Machines Corporation Research Division and Aggarwal, Charu C and Hinneburg, Alexander and Keim, Daniel},
title = {{On the Surprising Behavior of Distance Metrics in High Dimensional Space}},
year = {2000},
pages = {12}
}

@article{Nodelman:2005uh,
author = {Nodelman, Uri and Koller, Daphne},
title = {{Expectation propagation for continuous time Bayesian networks}},
journal = {UAI},
year = {2005}
}

@article{Thayananthan:2008iz,
author = {Thayananthan, Arasanathan and Navaratnam, Ramanan and Stenger, Bj{\"o}rn and Torr, Philip H S and Cipolla, Roberto},
title = {{Pose estimation and tracking using multivariate regression}},
journal = {Pattern Recognition Letters},
year = {2008},
volume = {29},
number = {9},
pages = {1302--1310},
month = jul,
annote = {<b>Terms to lookup</b>
RVM


<b>Review</b>
Pose estimation from silhouettes using templates. The main problem is formulated as learning one-to-many mapping functions that map from the feature space to the state space.

As the authors describe it: this paper has introduced a framework for single camera pose estimation and tracking that is a hybrid of learning based and generative model based approaches. So basically it is a whole lot of methods added up to create this framework which means it will take some time to go through this paper... }
}

@article{Tombari:2010cn,
author = {Tombari, Federico and Salti, Samuele and Stefano, Luigi},
title = {{Unique Signatures of Histograms for Local Surface Description}},
year = {2010},
volume = {6313},
number = {Chapter 26},
pages = {356--369}
}

@inproceedings{Hester:1999cp,
author = {Hester, R D and Cetin, M and Kapoor, C and Tesar, D},
title = {{A criteria-based approach to grasp synthesis}},
booktitle = {1999 IEEE International Conference on Robotics and Automation},
year = {1999},
pages = {1255--1260}
}

@article{Harnad:1999uv,
author = {Harnad, Stevan},
title = {{The Symbol Grounding Problem}},
journal = {CoRR cs.AI/9906002},
year = {1999}
}

@article{Roy:2005il,
author = {Roy, Deb},
title = {{Grounding words in perception and action: computational insights}},
journal = {Trends in Cognitive Sciences},
year = {2005},
volume = {9},
number = {8},
pages = {389--396},
month = aug
}

@article{Seeger:2005tl,
author = {Seeger, Mattias},
title = {{Expectation propagation for exponential families}},
journal = {Rapport technique},
year = {2005}
}

@article{Mackey:2012un,
author = {Mackey, L},
title = {{Matrix Factorization and Matrix Concentration}},
year = {2012}
}

@article{Asada:2009wn,
author = {Asada, M and Hosoda, K and Kuniyoshi, Y},
title = {{Cognitive Developmental Robotics: A Survey}},
journal = {Autonomous Mental {\ldots}},
year = {2009}
}

@article{Steingraber:eyWanu2C,
author = {Steingraber, Sandra},
title = {{Guidelines for Writing Scientific Papers}}
}

@article{Anandkumar:2012wb,
author = {Anandkumar, Animashree and Foster, Dean P and Hsu, Daniel and Kakade, Sham M and Liu, Yi-Kai},
title = {{Two SVDs Suffice: Spectral decompositions for probabilistic topic modeling and latent Dirichlet allocation}},
journal = {arXiv.org},
year = {2012},
eprint = {1204.6703v3},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = apr
}

@article{Burenius:Y0VsJmKq,
author = {Burenius, Magnus},
title = {{Human 3D Motion Computation from a Varying Number of Cameras }}
}

@article{Azizpour:wp,
author = {Azizpour, H and Laptev, I},
title = {{Object Detection Using Strongly-Supervised Deformable Part Models}},
journal = {csc.kth.se
}
}

@article{Zhang:2006hu,
author = {Zhang, J and Marsza{\l}ek, M and Lazebnik, S and Schmid, C},
title = {{Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study}},
journal = {International Journal of Computer Vision},
year = {2006},
volume = {73},
number = {2},
pages = {213--238},
month = sep
}

@article{Singh:2012tc,
author = {Singh, Satinder and James, Michael and Rudary, Matthew},
title = {{Predictive State Representations: A New Theory for Modeling Dynamical Systems}},
journal = {arXiv.org},
year = {2012},
eprint = {1207.4167v1},
eprinttype = {arxiv},
eprintclass = {cs.AI},
month = jul,
annote = {Appears in Proceedings of the Twentieth Conference on Uncertainty in
  Artificial Intelligence (UAI2004)}
}

@article{Barla:2003ix,
author = {Barla, Annalisa and Odone, Francesca and Verri, Alessandro},
title = {{Histogram intersection kernel for image classification.}},
journal = {ICIP},
year = {2003},
pages = {513--516}
}

@article{Dogar:2011tv,
author = {Dogar, M and Srinivasa, S},
title = {{A framework for push-grasping in clutter}},
journal = {Robotics: Science and Systems VII},
year = {2011}
}

@inproceedings{Hjelm:2013hr,
author = {Hjelm, Martin and Ek, Carl Henrik and Detry, Renaud and Kjellstr{\"o}m, Hedvig and Kragic, Danica},
title = {{Sparse summarization of robotic grasping data}},
booktitle = {2013 IEEE International Conference on Robotics and Automation},
year = {2013},
pages = {1082--1087},
publisher = {IEEE}
}

@article{Bengio:2013bu,
author = {Bengio, Y and Courville, A and Vincent, P},
title = {{Representation Learning: A Review and New Perspectives}},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
year = {2013},
volume = {35},
number = {8},
pages = {1798--1828}
}

@inproceedings{Diankov:2008cs,
author = {Diankov, R and Srinivasa, S S and Ferguson, Dave and Kuffner, J},
title = {{Manipulation planning with caging grasps}},
booktitle = {Humanoid Robots, 2008. Humanoids 2008. 8th IEEE-RAS International Conference on},
year = {2008},
pages = {285--292}
}

@book{Berger:1985vo,
author = {Berger, J O},
title = {{Statistical Decision Theory and Bayesian Analysis}},
year = {1985}
}

@article{Minka:2001vi,
author = {Minka, Thomas P},
title = {{Old and New Matrix Algebra Useful for Statistics}},
year = {2001}
}

@article{Zhang:2013vr,
author = {Zhang, Cheng and Ek, Carl Henrik and Kjellstr{\"o}m, Hedvig},
title = {{Factorized Topic Models}},
journal = {arXiv.org},
year = {2013},
eprint = {1301.3461v3},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = jan,
annote = {11 pages include 2 appendix pages}
}

@book{Sammut:2011to,
author = {Sammut, C and Webb, G I},
title = {{Encyclopedia of machine learning}},
publisher = {Springer},
year = {2011}
}

@article{Koppula:2012uy,
author = {Koppula, Hema Swetha and Gupta, Rudhir and Saxena, Ashutosh},
title = {{Learning Human Activities and Object Affordances from RGB-D Videos}},
journal = {arXiv.org},
year = {2012},
eprint = {1210.1207v1},
eprinttype = {arxiv},
eprintclass = {cs.RO},
month = oct,
annote = {arXiv admin note: substantial text overlap with arXiv:1208.0967}
}

@inproceedings{506534,
author = {Kamon, I and Flash, T and Edelman, S},
title = {{Learning to grasp using visual information}},
booktitle = {1996 IEEE International Conference on Robotics and Automation},
year = {1996},
pages = {2470--2476 vol.3}
}

@inproceedings{Lee:2009eg,
author = {Lee, D C and Hebert, M and Kanade, T},
title = {{Geometric reasoning for single image structure recovery}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2009 IEEE Conference on},
year = {2009},
pages = {2136--2143}
}

@inproceedings{Kang:1994dg,
author = {Kang, Sing Bing and Ikeuchi, K},
title = {{Robot task programming by human demonstration: mapping human grasps to manipulator grasps}},
booktitle = {1994 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {1994},
pages = {97--104}
}

@inproceedings{Boureau:2010kr,
author = {Boureau, Y L and Bach, F and LeCun, Y and Ponce, J},
title = {{Learning mid-level features for recognition}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on},
year = {2010},
pages = {2559--2566}
}

@article{Hedau:wz,
author = {Hedau, Varsha and Hoiem, Derek},
title = {{Recovering Free Space of Indoor Scenes from a Single Image}},
journal = {cs.illinois.edu
}
}

@article{Hoiem:2007do,
author = {Hoiem, Derek and Efros, Alexei A and Hebert, Martial},
title = {{Recovering Surface Layout from an Image}},
journal = {International Journal of Computer Vision},
year = {2007},
volume = {75},
number = {1},
pages = {151--172},
month = feb
}

@article{Aleotti:2010ci,
author = {Aleotti, Jacopo and Caselli, Stefano},
title = {{Interactive teaching of task-oriented robot grasps}},
journal = {Robotics and Autonomous Systems},
year = {2010},
volume = {58},
number = {5},
pages = {539--550},
month = may
}

@inproceedings{Jiang:vd,
author = {Jiang, Yun and Zheng, Changxi and Lim, M and Saxena, Ashutosh},
title = {{Learning to place new objects}},
booktitle = {2012 IEEE International Conference on Robotics and Automation},
year = {2012},
month = feb
}

@inproceedings{Romero:2010ex,
author = {Romero, J and Feix, T and Kjellstr{\"o}m, Hedvig and Kragic, Danica},
title = {{Spatio-temporal modeling of grasping actions}},
booktitle = {2010 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2010},
pages = {2103--2108}
}

@proceedings{Tenorth:N86nM32W,
title = {{Learning Probability Distributions over Partially-Ordered Human Everyday Activities}}
}

@inproceedings{Liu:2011ij,
author = {Liu, Lingqiao and Wang, Lei and Liu, Xinwang},
title = {{In defense of soft-assignment coding}},
booktitle = {Computer Vision (ICCV), 2011 IEEE International Conference on},
year = {2011},
pages = {2486--2493}
}

@article{Pauli:1998if,
author = {Pauli, Josef},
title = {{Learning to Recognize and Grasp Objects}},
journal = {Autonomous Robots},
year = {1998},
volume = {5},
number = {3/4},
pages = {407--420}
}

@article{Nguyen:2010tu,
author = {Nguyen, T D and Welsch, R E},
title = {{Outlier detection and robust covariance estimation using mathematical programming - Springer}},
journal = {Advances in Data Analysis and Classification},
year = {2010}
}

@inproceedings{Aleotti:2011hc,
author = {Aleotti, Jacopo and Caselli, Stefano},
title = {{Part-based robot grasp planning from human demonstration}},
booktitle = {2011 IEEE International Conference on Robotics and Automation},
year = {2011},
pages = {4554--4560},
annote = {
<b>Summary:</b>

Find a topological representation of objects, that is, a Reeb graph. Good thing about Reeb graphs is that they are invariant to rotation. Bad part is that they take time to compute. 

Clasify each object to belong to the class which is closests to the class protoype using the PATH algorithm.

Learn grasps with a glove. For each grasp represent it as set of the parts describing the object(I am guessing the nodes). Classify the grasped part as the one with most contact points. 

Learn a task precedence graph to learn the tasks. 

Select grasps from a set pre-defined grasps for the part being grasped.

I like this paper. However, it is unclear how good it will work in reality...






}
}

@article{Aghazadeh:wd,
author = {Aghazadeh, O and Azizpour, H and Sullivan, Josephine and Carlsson, Stefan},
title = {{Mixture Component Identification and Learning for Visual Recognition}},
journal = {csc.kth.se
}
}

@article{Anonymous:__ehOXt_,
title = {{Bayesian Inference}}
}

@article{Platt:1998wj,
author = {Platt, J},
title = {{Sequential minimal optimization: A fast algorithm for training support vector machines}},
year = {1998}
}

@article{Papazov:2011jm,
author = {Papazov, Chavdar and Burschka, Darius},
title = {{An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes}},
year = {2011},
volume = {6492},
number = {Chapter 11},
pages = {135--148}
}

@article{Wang:vc,
author = {Wang, Y and Thunberg, J and Hu, X},
title = {{A Transformation of the Position Based Visual Servoing Problem into a Convex Optimization Problem}},
journal = {csc.kth.se
}
}

@article{Damianou:2011vb,
author = {Damianou, Andreas C and Titsias, Michalis K and Lawrence, Neil D},
title = {{Variational Gaussian Process Dynamical Systems}},
journal = {arXiv.org},
year = {2011},
eprint = {1107.4985v1},
eprinttype = {arxiv},
eprintclass = {stat.ML},
month = jul,
annote = {16 pages, 19 figures}
}

@inproceedings{Tomovic:1987ia,
author = {Tomovic, R and Bekey, George A and Karplus, Walter J},
title = {{A strategy for grasp synthesis with multifingered robot hands}},
booktitle = {1987 IEEE International Conference on Robotics and Automation},
year = {1987},
pages = {83--89}
}

@inproceedings{Vedaldi:2011ek,
author = {Vedaldi, Andrea and Blaschko, Matthew B and Zisserman, Andrew},
title = {{Learning equivariant structured output SVM regressors}},
booktitle = {Computer Vision (ICCV), 2011 IEEE International Conference on},
year = {2011},
pages = {959--966}
}

@article{Wang:2008ia,
author = {Wang, J.M and Fleet, David J and Hertzmann, A},
title = {{Gaussian Process Dynamical Models for Human Motion}},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
year = {2008},
volume = {30},
number = {2},
pages = {283--298},
annote = {<b>First Read.</b>

<b>Review</b>
Some really interesting stuff...
}
}

@article{Dean:2013th,
author = {Dean, T and Ruzon, M A and Segal, M and Shlens, J},
title = {{Fast, Accurate Detection of 100,000 Object Classes on a Single Machine}},
journal = {{\ldots} on Computer {\ldots}},
year = {2013}
}

@book{Dasgupta:2006tx,
author = {Dasgupta, Sanjoy and Papadimitriou, Christos and Vazirani, Umesh},
title = {{Algorithms}},
publisher = {McGraw-Hill Science/Engineering/Math},
year = {2006},
edition = {McGraw-Hill Science/Engineering/Math},
month = sep
}

@inproceedings{Georgas:2008iv,
author = {Georgas, John C and Taylor, Richard N},
title = {{Policy-based self-adaptive architectures: a feasibility study in the robotics domain}},
booktitle = {SEAMS '08: Proceedings of the 2008 international workshop on Software engineering for adaptive and self-managing systems},
year = {2008},
publisher = { ACM},
month = may
}

@article{VanderMaaten:2008tm,
author = {Van der Maaten, LJP and Hinton, G},
title = {{Visualizing Data using t-SNE}},
journal = {Journal of Machine Learning Research},
year = {2008}
}

@inproceedings{Riedel:2013ve,
author = {Riedel, S and Yao, L and McCallum, A},
title = {{Relation Extraction with Matrix Factorization and Universal Schemas}},
booktitle = {Proceedings of NAACL- {\ldots}},
year = {2013}
}

@article{Zollner:2005ji,
author = {Z{\"o}llner, Raoul and Pardowitz, Michael and Knoop, Steffen and Dillmann, R{\"u}diger},
title = {{Towards Cognitive Robots: Building Hierarchical Task Representations of Manipulations from Human Demonstration.}},
journal = {ICRA},
year = {2005},
pages = {1535--1540}
}

@inproceedings{Dang:2012iu,
author = {Dang, Hao and Allen, Peter K},
title = {{Semantic grasping: Planning robotic grasps functionally suitable for an object manipulation task}},
booktitle = {2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2012},
pages = {1311--1317},
publisher = {IEEE}
}

@article{Turvey:1999tc,
author = {Turvey, M T and Shockley, K and Carello, C},
title = {{Affordance, proper function, and the physical basis of perceived heaviness}},
journal = {Cognition},
year = {1999}
}

@article{vonLuxburg:2007up,
author = {von Luxburg, Ulrike},
title = {{A Tutorial on Spectral Clustering}},
journal = {arXiv.org},
year = {2007},
eprint = {0711.0189v1},
eprinttype = {arxiv},
eprintclass = {cs.DS},
month = nov
}

@article{Niekum:us,
author = {Niekum, Scott and Osentoski, Sarah and Konidaris, George and Barto, Andrew G},
title = {{Learning and generalization of complex tasks from unstructured demonstrations}},
journal = {2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2012},
pages = {5239--5246}
}

@article{Romero:2012va,
author = {Romero, Javier and Feix, Thomas},
title = {{Extracting Postural Synergies for Robotic Grasping}},
year = {2012},
pages = {1--13},
month = nov
}

@article{Niekum:2011wd,
author = {Niekum, S and Barto, Andrew G},
title = {{Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery}},
journal = {Workshops at the Twenty-Fifth AAAI Conference on {\ldots}},
year = {2011}
}

@article{Granlund:2006jw,
author = {Granlund, G{\"o}sta H},
title = {{Organization of Architectures for Cognitive Vision Systems.}},
journal = {Cognitive Vision Systems},
year = {2006},
pages = {37--55}
}

@book{Gentle:2002th,
author = {Gentle, James},
title = {{Elements of Computational Statistics}},
publisher = {Springer},
year = {2002},
month = aug
}

@inproceedings{Fosgerau:2007jb,
author = {Fosgerau, Mogens},
title = {{Using nonparametrics to specify a model to measure the value of travel time}},
booktitle = {Transportation Research Part a-Policy and Practice},
year = {2007},
pages = {842--856}
}

@article{Antanas:2014uo,
author = {Antanas, Laura and Moreno, Plinio and Neumann, Marion and de Figueiredo, Rui Pimentel and Kersting, Kristian and Santos-Victor, Jos{\'e} and De Raedt, Luc},
title = {{High-level Reasoning and Low-level Learning for Grasping: A Probabilistic Logic Pipeline}},
journal = {arXiv.org},
year = {2014},
eprint = {1411.1108v1},
eprinttype = {arxiv},
eprintclass = {cs.RO},
month = nov
}

@article{Daoud:2012ub,
author = {Daoud, N and Gazeau, J P and Zeghloul, S and Arsicault, M},
title = {{A real-time strategy for dexterous manipulation: Fingertips motion planning, force sensing and grasp stability}},
journal = {Robotics and Autonomous {\ldots}},
year = {2012}
}

@article{Herzog:ww,
author = {Herzog, A and Pastor, P and Kalakrishnan, M and Righetti, L and Asfour, Tamin and Schaal, Stefan},
title = {{Template-based learning of grasp selection}},
journal = {2012 IEEE International Conference on Robotics and Automation}
}

@inproceedings{Miller:2003ev,
author = {Miller, A T and Knoop, S and Christensen, H I and Allen, Peter K},
title = {{Automatic grasp planning using shape primitives}},
booktitle = {2003 IEEE International Conference on Robotics and Automation},
year = {2003},
pages = {1824--1829}
}

@article{Seeger:2001tj,
author = {Seeger, Mattias and Williams, Christopher K I},
title = {{Using the Nystr{\"o}m Method to Speed Up Kernel Machines}},
journal = {{\ldots} in Neural Information Processing Systems 13},
year = {2001}
}

@article{Katz:2012wu,
author = {Katz, Dov and Kazemi, Moslem and Bagnell, J A and Stentz, Anthony},
title = {{Interactive Segmentation, Tracking, and Kinematic Modeling of Unknown Articulated Objects}},
year = {2012}
}

@article{Barrett:2008tt,
author = {Barrett, T M and Traupman, E and Needham, A},
title = {{Infants' visual anticipation of object structure in grasp planning}},
journal = {Infant behavior and development},
year = {2008}
}

@article{Koppula:2011tb,
author = {Koppula, H S and Anand, A and Joachims, Thorsten and Saxena, A},
title = {{Semantic Labeling of 3D Point Clouds for Indoor Scenes.}},
journal = {NIPS},
year = {2011}
}

@article{Norouzi:2013vi,
author = {Norouzi, M and Fleet, D},
title = {{Cartesian k-means}},
journal = {IEEE Conference on Computer Vision and {\ldots}},
year = {2013}
}

@inproceedings{Detry:2013ww,
author = {Detry, Renaud and Ek, Carl Henrik and Madry, Marianna and Kragic, Danica},
title = {{Learning a dictionary of prototypical grasp-predicting parts from grasping experience}},
booktitle = {2011 IEEE International Conference on Robotics and Automation},
year = {2013},
pages = {601--608},
publisher = {IEEE}
}

@article{Shlens:2005vi,
author = {Shlens, J},
title = {{A tutorial on principal component analysis}},
journal = {{\ldots} Neurobiology Laboratory},
year = {2005}
}

@article{Gupta:2K1yOY0g,
author = {Gupta, Maya R and Kapila, Amol and Frigyik, Bela A},
title = {{Introduction to the Dirichlet Distribution and Related Processes}}
}

@article{Domingos:2012te,
author = {Domingos, Pedro},
title = {{A few useful things to know about machine learning}},
journal = {Communications of the ACM},
year = {2012}
}

@article{Nickisch:2010vt,
author = {Nickisch, Hannes and Rasmussen, Carl Edward},
title = {{Gaussian Mixture Modeling with Gaussian Process Latent Variable Models}},
journal = {arXiv.org},
year = {2010},
eprint = {1006.3640v2},
eprinttype = {arxiv},
eprintclass = {stat.ML},
month = jun,
annote = {

<b>Review</b>
Not a very good paper in terms of general writing. Actually it is full of grammatical errors even some math errors etc. Overall the text poorly explains concepts and just moves around a lot. 

The authors begins to conclude that the GPVLM is not a good density model. By density model is meant the distribution over the observed data(here denoted as z)(Why do they use z btw? It is just irritating.). 

They then proceeds to formulate another training cost function than the log marginal likelihood since that cost function is focused on solving a regression scenario. The cost function the authors formulate is based on a general leave-out estimator. The leave-one-out scheme is implemented simply by removing the point x_i from the mean function, due to computational costs the point is not removed from the covariance. The authors also states that the one-to-one relationship in the GP is removed in the cost function. <b>In equation 2 this is evident since it is a Gaussian sum where each point is dependent on the means and covariances of all other points except itself.</b> Overfitting in density modeling means high density beeing assigned to training data while the test will have low density - I am guessing this means sort of a spiked density at training points in the GP regression. For the LOO cost function it is not enough to leave one point out so they leave out more than one. This will ensure that evening out of the probability mass across all points I am guessing.








 
















 }
}

@techreport{Francois:2004tk,
author = {Leray, Philippe and Francois, Olivier},
title = {{BNT structure learning package: documentation and experiments}},
institution = {Laboratoire PSI - INSA},
year = {2004}
}

@article{Osada:2002fa,
author = {Osada, Robert and Funkhouser, Thomas and Chazelle, Bernard and Dobkin, David},
title = {{Shape distributions}},
journal = {ACM Transactions on Graphics},
year = {2002},
volume = {21},
number = {4},
pages = {807--832},
month = oct
}

@article{Takeuchi:2006jn,
author = {Takeuchi, Jun-ichi and Yamanishi, Kenji},
title = {{A unifying framework for detecting outliers and change points from time series}},
journal = {Takeuchi, Jun-Ichi},
year = {2006},
volume = {18},
number = {4},
pages = {482--492}
}

@article{OHagan:1978vn,
author = {O'Hagan, A and Kingman, JFC},
title = {{Curve Fitting and Optimal Design for Prediction}},
journal = {Journal of the Royal Statistical Society Series B {\ldots}},
year = {1978}
}

@article{Berg:vq,
author = {Berg, T and Belhumeur, P N},
title = {{POOF: Part-Based One-vs-One Features for Fine-Grained Categorization, Face Verification, and Attribute Estimation}},
journal = {cs.columbia.edu
}
}

@article{Kuipers:1979uq,
author = {Kuipers, Benjamin J},
title = {{On Representing Commonsense Knowledge}},
journal = {{\ldots} networks: The representation and use of knowledge by {\ldots}},
year = {1979},
annote = {Summary: Philosophical essay on commonsense knowledge. The main problem formulation is: essential characteristics of a representation of commonsense knowledge and how to best form it so that it degrades gracefully under real world conditions. 

The author especially talks about: (1) The ability to express intermediate states of the learning process, (2) resilience in the face of partial destruction of the represented information and (3) the ability to express a meaningful response when a process is prematurely asked for the result of the computation.

In the conclusion he sets some measurements for quantitative analysis of any representation: 

- How resilient{\ldots}.under which destruction.
- Which sequences of observations can and cannot be represented completely.
- What kinds of partial information are usable{\ldots}for premature demands for an answer.
- How bad is a given class of disaster, for a given request in a given context?

}
}

@article{Wang:2009tf,
author = {Wang, R Y and Popovi{\'c}, Jovan},
title = {{Real-time hand-tracking with a color glove}},
journal = {ACM Transactions on Graphics (TOG)},
year = {2009},
annote = {


Review:
Uses a colored glove and a single camera to track hand pose by matching the segemented images to a database of color glove poses. Apparently in real-time.  

Again the idea of matching against a database of known hand poses.}
}

@proceedings{Katz:gu3Wz5aJ,
title = {{Interactive Segmentation, Tracking, and Kinematic Modeling of Unknown 3D Articulated Objects}}
}

@article{Bradley:1997cz,
author = {Bradley, Andrew P},
title = {{The use of the area under the ROC curve in the evaluation of machine learning algorithms}},
journal = {Pattern Recognition},
year = {1997},
volume = {30},
number = {7},
pages = {1145--1159},
month = jul
}

@article{Schneider:2014jr,
author = {Schneider, Sven and Hochgeschwender, Nico and Kraetzschmar, Gerhard K},
title = {{Declarative specification of task-based grasping with constraint validation.}},
journal = {IROS},
year = {2014},
pages = {919--926}
}

@article{VanderMaaten:2009vm,
author = {Van der Maaten, LJP and Postma, E O},
title = {{Dimensionality Reduction: A Comparative Review}},
journal = {Journal of Machine {\ldots}},
year = {2009}
}

@article{Kim:vl,
author = {Kim, J and Iwamoto, K and Kuffner, J J and Ota, Y and Pollard, N S},
title = {{Physically-based Grasp Quality Evaluation under Pose Uncertainty}},
journal = {cs.cmu.edu
}
}

@article{Parizi:2009tw,
author = {Parizi, S N and Targhi, A T and Aghazadeh, O},
title = {{Reading Street Signs Using a Generic Structured Object Detection and Signature Recognition Approach}},
journal = {{\ldots} Conference on Vision {\ldots}},
year = {2009}
}

@article{MatthewJBeal:2002tt,
author = {Matthew J Beal, Zoubin Ghahramani Carl Edward Rasmussen},
title = {{The Infinite Hidden Markov Model}},
year = {2002}
}

@inproceedings{Tang:2014bf,
author = {Tang, Danhang and Chang, Hyung Jin and Tejani, A and Kim, Tae-Kyun},
title = {{Latent Regression Forest: Structured Estimation of 3D Articulated Hand Posture}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on},
year = {2014},
pages = {3786--3793}
}

@inproceedings{Boularias:2011kt,
author = {Boularias, A and Kroemer, O and Peters, J},
title = {{Learning robot grasping from 3-D images with Markov Random Fields}},
booktitle = {2011 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2011},
pages = {1548--1553}
}

@inproceedings{Sun:2012ip,
author = {Sun, Min and Kohli, Pushmeet and Shotton, J},
title = {{Conditional regression forests for human pose estimation}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on},
year = {2012},
pages = {3394--3401}
}

@article{Granlund:2005ul,
author = {Granlund, G},
title = {{A cognitive vision architecture integrating neural networks with symbolic processing}},
journal = {K{\"u}nstliche Intelligenz},
year = {2005}
}

@article{Crawford:1989wg,
author = {Crawford, J M and Kuipers, Benjamin J},
title = {{Towards a Theory of Access-Limited Logic for Knowledge Representation.}},
journal = {KR},
year = {1989},
annote = {Summary: 

Delves into logic, especially what the authors describe as Access-Limited Logic which tries to describe commonsense knowledge to the end of limiting the set of possible deductions one can make. 

Not that interesting unless you want to get into the LISP and logic.
  }
}

@inproceedings{Griffiths:2004ey,
author = {Griffiths, Thomas L and Steyvers, M},
title = {{Finding scientific topics}},
booktitle = {Proceedings of the National Academy of Sciences of the United States of America},
year = {2004},
pages = {5228--5235},
organization = {Univ Calif Irvine, Dept Cognit Sci, Irvine, CA 92697 USA}
}

@inproceedings{Osada:2001gm,
author = {Osada, R and Funkhouser, T and Chazelle, B and Dobkin, D},
title = {{Matching 3D models with shape distributions}},
booktitle = {International Conference on Shape Modeling and Applications},
year = {2001},
pages = {154--166},
publisher = {IEEE Computer Society},
month = may
}

@article{Granlund:1999hp,
author = {Granlund, G{\"o}sta H},
title = {{The complexity of vision.}},
journal = {Signal Processing ()},
year = {1999},
volume = {74},
number = {1},
pages = {101--126}
}

@inproceedings{Rabiner:1989vx,
author = {Rabiner, L R},
title = {{A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition}},
booktitle = {Proceedings of the IEEE},
year = {1989}
}

@inproceedings{Liu:2014fd,
author = {Liu, M and Salzmann, Mathieu and He, Xuming},
title = {{Discrete-Continuous Depth Estimation from a Single Image}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on},
year = {2014},
pages = {716--723}
}

@article{Berthier:1996du,
author = {Berthier, Neil E and Clifton, Rachel K and Gullapalli, Vijaykumar and McCall, Daniel D and Robin, Daniel J},
title = {{Visual Information and Object Size in the Control of Reaching}},
journal = {Journal of Motor Behavior},
year = {1996},
volume = {28},
number = {3},
pages = {187--197},
month = sep
}

@article{Malisiewicz:2008cy,
author = {Malisiewicz, Tomasz and Efros, Alexei A},
title = {{Recognition by association via learning per-exemplar distances.}},
journal = {CVPR 2008},
year = {2008}
}

@article{Roberts:2009gv,
author = {Roberts, Gareth O and Rosenthal, Jeffrey S},
title = {{Examples of Adaptive MCMC}},
journal = {Journal of Computational and Graphical Statistics},
year = {2009},
volume = {18},
number = {2},
pages = {349--367},
month = jan
}

@article{Levin:2004bk,
author = {Levin, Anat and Lischinski, Dani and Weiss, Yair and Levin, Anat and Lischinski, Dani and Weiss, Yair},
title = {{Colorization using optimization}},
journal = {ACM Transactions on Graphics (TOG)},
year = {2004},
volume = {23},
number = {3},
pages = {689--694},
month = aug
}

@article{Tibshirani:1996um,
author = {Tibshirani, R},
title = {{JSTOR: Journal of the Royal Statistical Society. Series B (Methodological), Vol. 58, No. 1 (1996), pp. 267-288}},
journal = {Journal of the Royal Statistical Society Series B {\ldots}},
year = {1996}
}

@article{Tibshirani:2011ec,
author = {Tibshirani, Robert},
title = {{Regression shrinkage and selection via the lasso: a retrospective}},
journal = {Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
year = {2011},
volume = {73},
number = {3},
pages = {273--282},
month = apr
}

@article{MacKay:1998vv,
author = {MacKay, David},
title = {{Introduction to Monte Carlo Methods}},
journal = {NATO ASI SERIES D BEHAVIOURAL AND {\ldots}},
year = {1998}
}

@inproceedings{Baier:2006hc,
author = {Baier, T and Zhang, Jianwei},
title = {{Reusability-based Semantics for Grasp Evaluation in Context of Service Robotics}},
booktitle = {Robotics and Biomimetics, 2006. ROBIO '06. IEEE International Conference on},
year = {2006},
pages = {703--708}
}

@article{McCarty:1999wl,
author = {McCarty, M E and Ashmead, D H},
title = {{Visual control of reaching and grasping in infants.}},
journal = {Developmental psychology},
year = {1999},
volume = {35},
number = {3},
pages = {620--631},
month = may
}

@article{Kriegel:2008gn,
author = {Kriegel, Hans-Peter and Kr{\"o}ger, Peer and Schubert, Erich and Zimek, Arthur},
title = {{A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms}},
journal = {Scientific and Statistical {\ldots}},
year = {2008},
volume = {5069},
number = {Chapter 27},
pages = {418--435},
annote = {Some thoughts: Really good introduction. Pinpoints a lot of interesting things about dimensionality reduction!

Review: 

Adds a preprocessing or enhancement step to the PCA process. Basically it seems to discredit outliers...}
}

@article{Balaguer:tw,
author = {Balaguer, B and Carpin, S},
title = {{Human-Inspired Grasping of Novel Objects through Imitation Learning}},
journal = {research.bbalaguer.com
}
}

@article{Bustos:2005bo,
author = {Bustos, Benjamin and Keim, Daniel A and Saupe, Dietmar and Schreck, Tobias and Vrani{\'c}, Dejan V},
title = {{Feature-based similarity search in 3D object databases}},
journal = {ACM Computing Surveys},
year = {2005},
volume = {37},
number = {4},
pages = {345--387},
month = dec
}

@article{Yu:2005up,
author = {Yu, K and Tresp, V and Schwaighofer, A},
title = {{Learning Gaussian processes from multiple tasks}},
journal = {{\ldots} conference on Machine learning},
year = {2005}
}

@article{Hofmann:2007kf,
author = {Hofmann, Thomas and Sch{\"o}lkopf, Bernhard and Smola, Alexander J},
title = {{Kernel methods in machine learning}},
journal = {arXiv.org},
year = {2007},
eprint = {math/0701907v3},
eprinttype = {arxiv},
eprintclass = {math.ST},
month = jan,
annote = {Published in at http://dx.doi.org/10.1214/009053607000000677 the
  Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
  Mathematical Statistics (http://www.imstat.org)}
}

@inproceedings{Madry:wx,
author = {Madry, Marianna and Ek, Carl Henrik and Detry, Renaud and Hang, Kaiyu and Kragic, Danica},
title = {{Improving generalization for 3D object categorization with Global Structure Histograms}},
booktitle = {2012 IEEE/RSJ International Conference on Intelligent Robots and Systems}
}

@article{Cutkosky:1989wf,
author = {Cutkosky, M R},
title = {{On Grasp Choice, Grasp Models, and the Design of Hands for Manufacturing Tasks}},
journal = {Robotics {\&} Automation {\ldots}},
year = {1989}
}

@article{Greeno:1994wm,
author = {Greeno, J G},
title = {{Gibson's affordances}},
journal = {Psychological review},
year = {1994}
}

@inproceedings{Ganitkevitch:2013tf,
author = {Ganitkevitch, J and Van Durme, B},
title = {{Ppdb: The paraphrase database}},
booktitle = {Proceedings of NAACL- {\ldots}},
year = {2013}
}

@article{Jiang:2013we,
author = {Jiang, Y and Koppula, H and Saxena, A},
title = {{Hallucinated humans as the hidden context for labeling 3d scenes}},
year = {2013}
}

@article{Simon:2013ip,
author = {Simon, Noah and Friedman, Jerome and Hastie, Trevor and Tibshirani, Robert},
title = {{A Sparse-Group Lasso}},
journal = {Journal of Computational and Graphical Statistics},
year = {2013},
volume = {22},
number = {2},
pages = {231--245},
month = apr
}

@article{Montesano:2009wo,
author = {Montesano, L and Lopes, M},
title = {{Learning grasping affordances from local visual descriptors}},
journal = {{\ldots} and Learning},
year = {2009}
}

@article{Norman:1999ic,
author = {Norman, Donald A},
title = {{Affordance, conventions, and design}},
journal = {interactions},
year = {1999},
volume = {6},
number = {3},
pages = {38--43},
month = may
}

@article{Lawrence:2012tj,
author = {Lawrence, Neil D},
title = {{A Unifying Probabilistic Perspective for Spectral Dimensionality Reduction: Insights and New Models}},
journal = {The Journal of Machine Learning Research},
year = {2012},
volume = {98888},
pages = {1609--1638},
month = jun
}

@article{Payet:2012bk,
author = {Payet, N and Todorovic, S},
title = {{Hough Forest Random Field for Object Recognition and Segmentation}},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2012},
volume = {35},
number = {5},
pages = {1066--1079}
}

@article{Shahaf:2012wj,
author = {Shahaf, D and Guestrin, C and Horvitz, E},
title = {{Trains of thought: Generating Information Maps}},
journal = {{\ldots} of the 21st international conference on {\ldots}},
year = {2012}
}

@article{Remolina:1998vx,
author = {Remolina, E and Kuipers, Benjamin J},
title = {{Boundary region relations}},
journal = {Cognitive robotics},
year = {1998},
annote = {Summary: 

Deals with ontological hiearchies and finding boundary regions in toplogical map. Think subway maps and so on. A lot of logic and LISP. Not so interesting.

}
}

@article{Williams:1996wk,
author = {Williams, Christopher K I and Rasmussen, C E},
title = {{Gaussian processes for regression - Aston University Research Archive}},
year = {1996}
}

@article{Bilmes:1998tg,
author = {Bilmes, J A},
title = {{A gentle tutorial of the EM algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models}},
journal = {International Computer Science Institute},
year = {1998}
}

@webpage{Vardeman:oLbC-j_X,
author = {Vardeman, Steve},
title = {{Stat 602X Outline - Stat Tutorial}}
}

@inproceedings{Madry:2012tf,
author = {Madry, Marianna and Song, Dan and Kragic, Danica},
title = {{From object categories to grasp transfer using probabilistic reasoning}},
booktitle = {2011 IEEE International Conference on Robotics and Automation},
year = {2012},
pages = {1716--1723},
publisher = {IEEE}
}

@article{VanderMaaten:2007uu,
author = {Van der Maaten, LJP},
title = {{An Introduction to Dimensionality Reduction Using Matlab}},
journal = {Report},
year = {2007}
}

@article{Mian:2007jq,
author = {Mian, A S and Bennamoun, M and Owens, R},
title = {{An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition}},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
year = {2007},
volume = {29},
number = {11},
pages = {1927--1943}
}

@article{Li:2006hm,
author = {Li, Tao and Zhu, Shenghuo and Ogihara, Mitsunori},
title = {{Using discriminant analysis for multi-class classification: an experimental investigation}},
journal = {Knowledge and Information Systems},
year = {2006},
volume = {10},
number = {4},
pages = {453--472},
month = mar
}

@article{Bergstrom:2012vl,
author = {Bergstr{\"o}m, Niklas},
title = {{Interactive Perception : From Scenes to Objects}},
year = {2012},
pages = {viii--135}
}

@inproceedings{Sivic:2008tp,
author = {Sivic, J and Zisserman, Andrew},
title = {{Efficient Visual Search for Objects in Videos}},
booktitle = {Proceedings of the IEEE},
year = {2008}
}

@article{Chen:2006ca,
author = {Chen, Lijun and Georganas, Nicolas D},
title = {{An efficient and robust algorithm for 3D mesh segmentation}},
journal = {Multimedia Tools and Applications},
year = {2006},
volume = {29},
number = {2},
pages = {109--125},
month = jun
}

@article{Ciocarlie:2010tf,
author = {Ciocarlie, Matei and Hsiao, Kaijen and Jones, E Gil and Chitta, Sachin and Rusu, Radu Bogdan and Sucan, Ioan A},
title = {{Towards reliable grasping and manipulation in household environments}},
journal = {New Delhi, India},
year = {2010},
volume = {12},
pages = {2010}
}

@article{Vandenberghe:1996te,
author = {Vandenberghe, Lieven and Boyd, Stephen},
title = {{Semidefinite Programming}},
journal = {dx.doi.org},
year = {1996}
}

@article{Steele:2009tl,
author = {Steele, R J},
title = {{Performance of bayesian model selection criteria for gaussian mixture models}},
journal = {Dept Stat},
year = {2009}
}

@inproceedings{Aghazadeh:ug,
author = {Aghazadeh, O and Sullivan, Josephine and Carlsson, Stefan},
title = {{Novelty detection from an ego-centric perspective}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on}
}

@article{Quiroga:2012dq,
author = {Quiroga, Rodrigo Quian},
title = {{Concept cells: the building blocks of declarative memory functions}},
journal = {Nature Reviews Neuroscience},
year = {2012},
volume = {13},
number = {8},
pages = {587--597},
month = jul
}

@article{Saxena:2009gt,
author = {Saxena, A and Min Sun and Ng, Andrew Y.},
title = {{Make3D: Learning 3D Scene Structure from a Single Still Image}},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2009},
volume = {31},
number = {5},
pages = {824--840},
month = may
}

@article{Kuipers:1984vs,
author = {Kuipers, Benjamin J},
title = {{Commonsense reasoning about causality: Deriving behavior from structure}},
journal = {Artificial Intelligence Review},
year = {1984}
}

@article{Chinellato:2006hh,
author = {Chinellato, Eris and Recatal{\'a}, Gabriel and del Pobil, Angel P and Mezouar, Youcef and Martinet, Philippe},
title = {{3D Grasp Synthesis Based on Object Exploration.}},
journal = {ROBIO},
year = {2006},
pages = {1065--1070}
}

@article{Ek:wn,
author = {Ek, Carl Henrik and Song, Dan and Kragic, Danica},
title = {{Learning Conditional Structures in Graphical Models from a Large Set of Observation Streams through efficient Discretisation}},
journal = {IEEE International Conference {\ldots}},
year = {2011}
}

@article{Kemp:2007tj,
author = {Kemp, C C and Edsinger, A},
title = {{Challenges for robot manipulation in human environments [grand challenges of robotics]}},
journal = {Robotics {\&} Automation {\ldots}},
year = {2007}
}

@article{Lenz:2013uz,
author = {Lenz, Ian and Lee, Honglak and Saxena, Ashutosh},
title = {{Deep Learning for Detecting Robotic Grasps}},
journal = {arXiv.org},
year = {2013},
eprint = {1301.3592v5},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = jan
}

@article{Anandkumar:2012uv,
author = {Anandkumar, Animashree and Hsu, Daniel and Kakade, Sham M},
title = {{Learning High-Dimensional Mixtures of Graphical Models}},
journal = {arXiv.org},
year = {2012},
eprint = {1203.0697v1},
eprinttype = {arxiv},
eprintclass = {stat.ML},
month = mar
}

@article{Wolfson:1997br,
author = {Wolfson, H J and Rigoutsos, I},
title = {{Geometric hashing: an overview}},
journal = {Computational Science {\&} Engineering, IEEE},
year = {1997},
volume = {4},
number = {4},
pages = {10--21}
}

@article{Song:2010gh,
author = {Song, Dan and Huebner, Kai and Kyrki, Ville and Kragic, Danica},
title = {{Learning task constraints for robot grasping using graphical models.}},
journal = {IROS},
year = {2010},
pages = {1579--1585}
}

@inproceedings{Jegou:2010hf,
author = {Jegou, H and Douze, M and Schmid, C and Perez, P},
title = {{Aggregating local descriptors into a compact image representation}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on},
year = {2010},
pages = {3304--3311}
}

@book{Theodorids:b2wT4Y8r,
author = {Theodorids, Sergios and Koutroumbas, Konstantinos},
title = {{Pattern Recognition}},
edition = {4}
}

@book{vanHandel:x4rtQR-W,
author = {van Handel, Roman},
title = {{Hidden Markov Models - Lecture notes}}
}

@article{Bohg:H95zG3Ya,
author = {Bohg, Jeannette and Morales, Antonio and Asfour, Tamin and Kragic, Danica},
title = {{Data-Driven Grasp Synthesis - A Survey}}
}

@book{Orlande:OBtNA-CJ,
author = {Orlande, Hedi},
title = {{Kalman and Particle Filters - Lecture notes}}
}

@inproceedings{Attias:1999wv,
author = {Attias, Hagai},
title = {{Inferring parameters and structure of latent variable models by variational bayes}},
booktitle = {UAI'99: Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence},
year = {1999},
publisher = { Morgan Kaufmann Publishers Inc},
month = jul
}

@article{Aghazadeh:2012va,
author = {Aghazadeh, O and Sullivan, Josephine},
title = {{Multi View Registration for Novelty/Background Separation}},
journal = {Computer Vision and Pattern  {\ldots}},
year = {2012}
}

@inproceedings{Tsochantaridis:2004bd,
author = {Tsochantaridis, Ioannis and Hofmann, Thomas and Joachims, Thorsten and Altun, Yasemin},
title = {{Support vector machine learning for interdependent and structured output spaces}},
booktitle = {ICML '04: Proceedings of the 21st Annual International Conference on Machine Learning},
year = {2004},
pages = {104},
publisher = {ACM Press},
address = {New York, New York, USA}
}

@article{Plagemann:2008up,
author = {Plagemann, Christian},
title = {{FreiDok - Gaussian processes for flexible robot learning}},
journal = {SWB-IDNR/289109833},
year = {2008}
}

@article{Hershey:2014ta,
author = {Hershey, John R and Le Roux, Jonathan and Weninger, Felix},
title = {{Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures}},
journal = {arXiv.org},
year = {2014},
eprint = {1409.2574v4},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = sep,
annote = {Added sections on reducing belief propagation to network activation
  functions, and on conversion between conventional network parameters and BP
  potentials for binary MRFs. Some bugs and typos were also fixed, and notation
  made a bit clearer}
}

@article{Yang:2014vd,
author = {Yang, Zichao and Moczulski, Marcin and Denil, Misha and de Freitas, Nando and Smola, Alex and Le Song and Wang, Ziyu},
title = {{Deep Fried Convnets}},
journal = {arXiv.org},
year = {2014},
eprint = {1412.7149v2},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = dec,
annote = {revision after review}
}

@article{Cousineau:2010tk,
author = {Cousineau, D and Chartier, S},
title = {{Outliers detection and treatment: A review}},
journal = {International Journal of Psychological {\ldots}},
year = {2010}
}

@article{Herzog:2013fh,
author = {Herzog, Alexander and Pastor, Peter and Kalakrishnan, Mrinal and Righetti, Ludovic and Bohg, Jeannette and Asfour, Tamim and Schaal, Stefan},
title = {{Learning of grasp selection based on shape-templates}},
journal = {Autonomous Robots},
year = {2013},
volume = {36},
number = {1-2},
pages = {51--65},
month = sep
}

@inproceedings{Hillenbrand:2012im,
author = {Hillenbrand, U and Roa, M A},
title = {{Transferring functional grasps through contact warping and local replanning}},
booktitle = {2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2012},
pages = {2963--2970}
}

@article{Anandkumar:2012ut,
author = {Anandkumar, Animashree and Hsu, Daniel and Kakade, Sham M},
title = {{A Method of Moments for Mixture Models and Hidden Markov Models}},
journal = {arXiv.org},
year = {2012},
eprint = {1203.0683v1},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = mar
}

@article{Opper:2010vc,
author = {Csat{\'o}, Lehel and Opper, Manfred},
title = {{Sparse Gaussian Processes: Inference And Model Selection}},
year = {2010}
}

@article{Jarosz:2011jg,
author = {Jarosz, Wojciech and Nowrouzezahrai, Derek and Sadeghi, Iman and Jensen, Henrik Wann},
title = {{A comprehensive theory of volumetric radiance estimation using photon points and beams}},
journal = {Transactions on Graphics (TOG},
year = {2011},
volume = {30},
number = {1},
month = jan
}

@article{Wagstaff:2012tr,
author = {Wagstaff, Kiri},
title = {{Machine Learning that Matters}},
journal = {arXiv.org},
year = {2012},
eprint = {1206.4656v1},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = jun
}

@inproceedings{Modayil:2004cl,
author = {Modayil, J and Kuipers, Benjamin J},
title = {{Bootstrap learning for object discovery}},
booktitle = {2004 IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2004},
pages = {742--747},
annote = {<b>Summary: </b>

Basically simple learning of environments and objects. Deals with creating categories out of several snapshots of objecs from a laser range finder. The clustering is using a simple distance measure. 

<b>Relation to my work:</b> Not really related at all other than some kind of categorization. There is some interesting preprocessing stuff for clustering the images.
 
}
}

@article{deGranville:2006uz,
author = {de Granville, C and Southerland, J and Fagg, A H},
title = {{Learning grasp affordances through human demonstration}},
journal = {{\ldots} Development and Learning ( {\ldots}},
year = {2006}
}

@article{Seeger:2003th,
author = {Seeger, Mattias},
title = {{Bayesian Gaussian process models: PAC-Bayesian generalisation error bounds and sparse approximations}},
year = {2003}
}

@article{Arandjelovic:vi,
author = {Arandjelovic, R and Zisserman, Andrew},
title = {{All about VLAD}},
journal = {lucca.robots.ox.ac.uk
}
}

@article{Corduneanu:2001ve,
author = {Corduneanu, A and Bishop, Christopher M},
title = {{Variational Bayesian model selection for mixture distributions}},
journal = {Artificial intelligence and {\ldots}},
year = {2001}
}

@inproceedings{Saxena:2007bl,
author = {Saxena, Ashutosh and Sun, Min and Ng, Andrew Y.},
title = {{Learning 3-D Scene Structure from a Single Still Image}},
booktitle = {2007 IEEE International Conference on Computer Vision},
year = {2007},
pages = {1--8},
publisher = {IEEE}
}

@article{Tsochantaridis:2006ww,
author = {Tsochantaridis, Ioannis and Joachims, Thorsten and Hofmann, T},
title = {{Large margin methods for structured and interdependent output variables}},
journal = {Journal of Machine {\ldots}},
year = {2006}
}

@article{Titsias:wp,
author = {Titsias, Michalis K and Lawrence, Neil D},
title = {{Variational Bayes Sparse Multiple Output Gaussian Processes}},
journal = {cs.man.ac.uk
}
}

@inproceedings{Abdo:2013vq,
author = {Abdo, Nichola and Kretzschmar, Henrik and Spinello, Luciano and Stachniss, Cyrill},
title = {{Learning manipulation actions from a few demonstrations}},
booktitle = {2013 IEEE International Conference on Robotics and Automation},
year = {2013},
pages = {1268--1275},
publisher = {IEEE},
annote = {Review: 

In this paper the authors work on task planning. They reason that the robot should recognize pre-states and post-states of the task to be able to do high-level planning.

The authors use learning by demonstration. Basic actions are learned by moving the robot arm recording the movements. 

Preconditions 
The authors argue that preconditions must be flexible. By making the features independent to each other with relation to the specific action the can vary the possible pre-conditional states. In order to detect  irrelevant conditions they compare feature variance - regarding small variations as an indicator for relevance. The same holds for effects of actions.

The feature variance detection is done by clustering the feature space for a number of clusters, K. For each possible clustering they  sum the intra cluster distances to its mean, and if this value is lower than a specific value for some K then the feature is relevant for the action. To judge if a certain feature fulfills the condition its distance to the mean is calculated and if it is below a threshold then it is considered fulfilled. 







}
}

@article{deGranville:2008ux,
author = {de Granville, C},
title = {{Learning grasp affordances}},
year = {2008},
annote = {Has some interesting notions of how to formulate probability distributions over objects plus one for objects that are symmetrical around an axis. Might not be so relevant to the task constraint since our pdf's are readings of local conditions.
One problem is also that the assume {\'a} priori known object models or rather that model they learn is per object. They do learn a distribution for gripper pose + finger placement over the object based upon human demonstration, however, the model is per object and does not generalize it seems.
The ICL or BIC criterion might be an interesting approach to prune the number of inducing points in the GPLVM-cluster method.}
}

@article{Cunningham:2012te,
author = {Cunningham, J and Ghahramani, Zoubin},
title = {{Gaussian Processes for time-marked time-series data}},
journal = {International {\ldots}},
year = {2012}
}

@article{Kuipers:2005ty,
author = {Kuipers, Benjamin J},
title = {{Consciousness: Drinking from the Firehose of Experience (revised and expanded)}},
year = {2005},
annote = {<b>Summary:</b>

Deals with the subject of consciousness and how it relates to a robotic / computational perspective on it. 

Could be interesting to read again a bit more thorough.
}
}

@article{Kraft:2010jw,
author = {Kraft, D and Detry, Renaud and Pugeault, N and Bas x0327 eski, E and Guerin, F and Piater, J H and Kr{\"u}ger, Norbert},
title = {{Development of Object and Grasping Knowledge by Robot Exploration}},
journal = {Autonomous Mental Development, IEEE Transactions on},
year = {2010},
volume = {2},
number = {4},
pages = {368--383}
}

@inproceedings{Aleotti:2011jt,
author = {Aleotti, J and Caselli, S},
title = {{Manipulation planning of similar objects by part correspondence}},
booktitle = {Advanced Robotics (ICAR), 2011 15th International Conference on},
year = {2011},
pages = {247--252},
publisher = {IEEE}
}

@book{Rasmussen:2006vz,
author = {Rasmussen, Carl Edward and Williams, Christopher K I},
title = {{Gaussian Processes for Machine Learning}},
publisher = {The MIT Press},
year = {2006}
}

@book{Lehman:24auOydD,
author = {Lehman, Eric and Leighton, Tom},
title = {{Mathematics for Computer Science}}
}

@book{Cormen:U42AKFYg,
author = {Cormen, Thomas and Leiserson, Charles and Rivest, Ronald and Stein, Clifford},
title = {{Introduction to Algorithms}}
}

@article{Hurley:2008er,
author = {Hurley, N and Rickard, S},
title = {{Comparing measures of sparsity}},
journal = {Machine Learning for Signal Processing, 2008. MLSP 2008. IEEE Workshop on},
year = {2008},
pages = {55--60}
}

@article{Iwata:2012vo,
author = {Iwata, Tomoharu and Duvenaud, David and Ghahramani, Zoubin},
title = {{Nonparametric Bayesian Clustering via Infinite Warped Mixture Models}},
journal = {arXiv.org},
year = {2012},
eprint = {1206.1846v1},
eprinttype = {arxiv},
eprintclass = {stat.ML},
month = jun,
annote = {9 pages, 5 figures}
}

@article{Titsias:2010tb,
author = {Titsias, Michalis K and Lawrence, Neil D},
title = {{Bayesian Gaussian Process Latent Variable Model}},
journal = {Artificial Intelligence Review},
year = {2010},
volume = {9},
pages = {844--851}
}

@inproceedings{Funda:1988df,
author = {Funda, J and Paul, R P},
title = {{A comparison of transforms and quaternions in robotics}},
booktitle = {1988 IEEE International Conference on Robotics and Automation},
year = {1988},
pages = {886--891}
}

@article{Kuipers:2006ex,
author = {Kuipers, Benjamin J and Beeson, Patrick and Modayil, Joseph and Provost, Jefferson},
title = {{Bootstrap learning of foundational representations}},
journal = {Connection Science},
year = {2006},
volume = {18},
number = {2},
pages = {145--158},
month = jun
}

@article{Jin:2012hx,
author = {Jin, Yong and Wu, Qingbiao and Liu, Ligang},
title = {{Unsupervised upright orientation of man-made models}},
journal = {Graphical Models},
year = {2012},
volume = {74},
number = {4},
pages = {99--108},
month = jul
}

@article{Kong:1995wx,
author = {Kong, EB},
title = {{Machine learning bias, statistical bias, and statistical variance of decision tree algorithms}},
journal = {ML-95},
year = {1995}
}

@techreport{Rosenthal08optimalproposal,
author = {Rosenthal, Jeffrey S},
title = {{Optimal Proposal Distributions and Adaptive MCMC}},
year = {2008}
}

@book{Eckford:kOujoQUM,
author = {Eckford, Andrew},
title = {{Molecular Communication}}
}

@book{norman2002design,
author = {Norman, D A},
title = {{The Design of Everyday Things}},
publisher = {Basic Books},
year = {2002}
}

@inproceedings{Kuettel:2012it,
author = {Kuettel, D and Ferrari, V},
title = {{Figure-ground segmentation by transferring window masks}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on},
year = {2012},
pages = {558--565}
}

@article{Agarwal:2006hh,
author = {Agarwal, A and Triggs, B},
title = {{Recovering 3D human pose from monocular images}},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
year = {2006},
volume = {28},
number = {1},
pages = {44--58}
}

@article{Belanger:2012wn,
author = {Belanger, D and Passos, A and Riedel, S},
title = {{Map inference in chains using column generation}},
journal = {Advances in Neural Information Processing Systems {\ldots}},
year = {2012}
}

@article{Rosenstein:2005wg,
author = {Rosenstein, M T and Marx, Z and Kaelbling, L P},
title = {{To transfer or not to transfer}},
journal = {{\ldots} on Inductive Transfer},
year = {2005}
}

@article{Bohg:2010es,
author = {Bohg, Jeannette and Kragic, Danica},
title = {{Learning grasping points with shape context}},
journal = {Robotics and Autonomous Systems},
year = {2010},
volume = {58},
number = {4},
pages = {362--377},
month = apr
}

@article{Eaton:2006wj,
author = {Eaton, E and Desjardins, M},
title = {{Knowledge transfer with a multiresolution ensemble of classifiers}},
journal = {{\ldots} Knowledge Transfer for Machine Learning},
year = {2006}
}

@inproceedings{Schmidt:2012iv,
author = {Schmidt, Uwe and Roth, Stefan},
title = {{Learning rotation-aware features: From invariant priors to equivariant descriptors}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on},
year = {2012},
pages = {2050--2057}
}

@article{Aghazadeh:tz,
author = {Aghazadeh, O and Sullivan, Josephine and Carlsson, Stefan},
title = {{Automatic Memory Selection via Novelty Detection}},
journal = {csc.kth.se
}
}

@article{Seeger:2003wo,
author = {Seeger, Mattias and Williams, Christopher K I and Lawrence, Neil D},
title = {{Fast forward selection to speed up sparse Gaussian process regression}},
journal = {Workshop on AI and  {\ldots}},
year = {2003}
}

@book{Riggelsen:2007vz,
author = {Riggelsen, Carsten},
title = {{Approximation Methods for Efficient Learning of Bayesian Networks}},
publisher = {Ios Pr Incorporated},
year = {2007},
month = nov
}

@article{Detry:2013wd,
author = {Detry, Renaud and Piater, Justus},
title = {{Unsupervised learning of predictive parts for cross-object grasp transfer}},
year = {2013},
pages = {1720--1727}
}

@inproceedings{Modayil:2007uu,
author = {Modayil, J and Kuipers, Benjamin J},
title = {{Autonomous development of a grounded object ontology by a learning robot}},
booktitle = {Proceedings of the national conference on Artificial {\ldots}},
year = {2007}
}

@article{Collet:2011df,
author = {Collet, A and Martinez, M and Srinivasa, S S},
title = {{The MOPED framework: Object recognition and pose estimation for manipulation}},
journal = {The International Journal of Robotics Research},
year = {2011},
volume = {30},
number = {10},
pages = {1284--1306},
month = sep
}

@article{Bekey:1993jd,
author = {Bekey, George A and Liu, H and Tomovic, R and Karplus, Walter J},
title = {{Knowledge-based control of grasping in robot hands using heuristics from human motor skills}},
journal = {Robotics and Automation, IEEE Transactions on},
year = {1993},
volume = {9},
number = {6},
pages = {709--722}
}

@inproceedings{Schwing:2012fp,
author = {Schwing, Alexander G and Hazan, Tamir and Pollefeys, Marc and Urtasun, Raquel},
title = {{Efficient structured prediction for 3D indoor scene understanding}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on},
year = {2012},
pages = {2815--2822}
}

@article{Krizhevsky:2012wl,
author = {Krizhevsky, A and Sutskever, I and Hinton, G},
title = {{Imagenet classification with deep convolutional neural networks}},
journal = {Advances in Neural Information {\ldots}},
year = {2012}
}

@article{Cao:2010uz,
author = {Cao, Longbing and Philip, S Yu and Zhang, Chengqi and Zhao, Yanchang},
title = {{Domain driven data mining}},
year = {2010}
}

@article{Murphy:1998to,
author = {Murphy, KP},
title = {{Fitting a conditional linear Gaussian distribution}},
year = {1998}
}

@article{Geng:2011gw,
author = {Geng, Bo and Tao, Dacheng and Xu, Chao},
title = {{DAML: Domain Adaptation Metric Learning}},
journal = {Image Processing, IEEE Transactions on},
year = {2011},
volume = {20},
number = {10},
pages = {2980--2989}
}

@article{Hermans:2011vz,
author = {Hermans, T and Rehg, J M and Bobick, A},
title = {{Affordance prediction via learned object attributes}},
journal = {{\ldots} of the IEEE International Conference on {\ldots}},
year = {2011}
}

@article{Ion:2011vb,
author = {Ion, A and Carreira, J},
title = {{Probabilistic Joint Image Segmentation and Labeling}},
journal = {Advances in Neural Information Processing Systems {\ldots}},
year = {2011}
}

@inproceedings{Bohg:2012wv,
author = {Bohg, Jeannette and Welke, Kai and Le{\'o}n, Beatriz and Do, Martin and Song, Dan and Wohlkinger, Walter and Madry, Marianna and Ald{\'o}ma, Aitor and Przybylski, Markus and Asfour, Tamim and Kragic, Danica},
title = {{Task-based Grasp Adaptation on a Humanoid Robot}},
booktitle = {10th International IFAC Symposium on Robot Control (SYROCO), Dubrovnik, Croatia on September 05-07, 2012},
year = {2012},
pages = {779--786}
}

@inproceedings{Branson:2011ht,
author = {Branson, Steve and Perona, Pieriro and Belongie, Serge J},
title = {{Strong supervision from weak annotation: Interactive training of deformable part models}},
booktitle = {Computer Vision (ICCV), 2011 IEEE International Conference on},
year = {2011},
pages = {1832--1839}
}

@article{Srivastava:2012vd,
author = {Srivastava, N and Salakhutdinov, R},
title = {{Multimodal learning with deep Boltzmann machines}},
journal = {Advances in Neural Information {\ldots}},
year = {2012}
}

@phdthesis{Modayil:2007tv,
author = {Modayil, J V},
title = {{Robot Developmental Learning of an Object Ontology Grounded in Sensorimotor}},
school = {University of Texas at Austin},
year = {2007}
}

@article{Lawrence:2007vt,
author = {Lawrence, Neil D},
title = {{Learning for Larger Datasets with the Gaussian Process Latent Variable Model}},
year = {2007}
}

@article{Gordon:1995uo,
author = {Gordon, Df and Desjardins, M},
title = {{Evaluation and Selection of Biases in Machine Learning}},
journal = {Machine Learning},
year = {1995},
volume = {20},
pages = {5--22}
}

@inproceedings{Karpathy:2014kq,
author = {Karpathy, A and Toderici, G and Shetty, S and Leung, T and Sukthankar, R and Fei-Fei, Li},
title = {{Large-Scale Video Classification with Convolutional Neural Networks}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on},
year = {2014},
pages = {1725--1732}
}

@article{Bengio:2003vh,
author = {Bengio, Yoshua and Ducharme, R{\'e}jean and Vincent, Pascal and Janvin, Christian},
title = {{A neural probabilistic language model}},
journal = {The Journal of Machine Learning Research},
year = {2003},
volume = {3},
pages = {1137--1155},
month = mar
}

@inproceedings{Sinapov:2008dt,
author = {Sinapov, J and Stoytchev, A},
title = {{Detecting the functional similarities between tools using a hierarchical representation of outcomes}},
booktitle = {Development and Learning, 2008. ICDL 2008. 7th IEEE International Conference on},
year = {2008},
pages = {91--96}
}

@article{Held:1963us,
author = {Held, Richard and Hein, Alan},
title = {{Movement-produced stimulation in the development of visually guided behavior}},
journal = {Journal of Comparative and Physiological Psychology},
year = {1963},
volume = {56},
pages = {872--876},
month = apr
}

@inproceedings{Mugan:2007ix,
author = {Mugan, J and Kuipers, Benjamin J},
title = {{Learning to predict the effects of actions: Synergy between rules and landmarks}},
booktitle = {Development and Learning, 2007. ICDL 2007. IEEE 6th International Conference on},
year = {2007},
pages = {253--258}
}

@inproceedings{Ren:2013dc,
author = {Ren, Xiaofeng and Ramanan, D},
title = {{Histograms of Sparse Codes for Object Detection}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on},
year = {2013},
pages = {3246--3253}
}

@article{Koppula:2013ij,
author = {Koppula, H S and Gupta, R and Saxena, A},
title = {{Learning human activities and object affordances from RGB-D videos}},
journal = {The International Journal of Robotics Research},
year = {2013},
volume = {32},
number = {8},
pages = {951--970},
month = jul
}

@article{Wang:wb,
author = {Wang, T and He, X and Barnes, N},
title = {{Learning Structured Hough Voting for Joint Object Detection and Occlusion Reasoning}},
journal = {users.cecs.anu.edu.au
}
}

@article{Aghazadeh:wc,
author = {Aghazadeh, O and Sullivan, Josephine and Carlsson, Stefan},
title = {{Novelty Detection in Wearable Visual Systems}},
journal = {csc.kth.se
}
}

@inproceedings{ElNasr:2004gp,
author = {El-Nasr, Magy Seif},
title = {{A user-centric adaptive story architecture: borrowing from acting theories}},
booktitle = {ACE '04: Proceedings of the 2004 ACM SIGCHI International Conference on Advances in computer entertainment technology},
year = {2004},
publisher = { ACM},
month = sep
}

@article{He:tj,
author = {He, K and Sun, J},
title = {{Statistics of Patch Offsets for Image Completion}},
journal = {research.microsoft.com
}
}

@book{gibson2014ecological,
author = {Gibson, J J},
title = {{The Ecological Approach to Visual Perception: Classic Edition}},
year = {2014},
series = {Psychology Press}
}

@article{Montesano:2008dg,
author = {Montesano, L and Lopes, M and Bernardino, A and Santos-Victor, Jos{\'e}},
title = {{Learning Object Affordances: From Sensory-Motor Coordination to Imitation}},
journal = {Robotics, IEEE Transactions on},
year = {2008},
volume = {24},
number = {1},
pages = {15--26}
}

@article{Wohlhart:vj,
author = {Wohlhart, P and K{\"o}stinger, M and Donoser, M and Roth, P M},
title = {{Optimizing 1-Nearest Prototype Classifiers}},
journal = {researchgate.net
}
}

@inproceedings{Vedaldi:2009jz,
author = {Vedaldi, Andrea and Gulshan, Varun and Varma, Manik and Zisserman, Andrew},
title = {{Multiple kernels for object detection}},
booktitle = {Computer Vision, 2009 IEEE 12th International Conference on},
year = {2009},
pages = {606--613}
}

@inproceedings{Collet:2009km,
author = {Collet, Alvaro and Berenson, Dmitry and Srinivasa, Siddhartha S and Ferguson, Dave},
title = {{Object recognition and full pose registration from a single image for robotic manipulation}},
booktitle = {2009 IEEE International Conference on Robotics and Automation},
year = {2009},
pages = {48--55},
publisher = {IEEE}
}

@phdthesis{Aghazadeh:6VS8RDK-,
author = {Aghazadeh, O},
title = {{Object Segmentation using Spatial and Spatio-Temporal features}}
}

@article{Vondrick:2013wj,
author = {Vondrick, C and Khosla, A and Malisiewicz, T},
title = {{HOG-gles: Visualizing Object Detection Features}},
journal = {{\ldots} Vision (ICCV)},
year = {2013}
}

@article{Felzenszwalb:2004vi,
author = {Felzenszwalb, P F and Huttenlocher, D P},
title = {{Efficient Graph-Based Image Segmentation - Springer}},
journal = {International Journal of Computer {\ldots}},
year = {2004}
}

@article{Kuipers:2007tk,
author = {Kuipers, Benjamin J},
title = {{Sneaking up on the Hard Problem of consciousness}},
journal = {Proc AAAI Symp Machine Consciousness and AI},
year = {2007}
}

@article{daFonseca:2007ih,
author = {da Fonseca, C M},
title = {{On the eigenvalues of some tridiagonal matrices}},
journal = {Journal of Computational and Applied Mathematics},
year = {2007},
volume = {200},
number = {1},
pages = {283--286},
month = mar
}

@article{Vogel:2007eg,
author = {Vogel, Julia and Schwaninger, Adrian and Wallraven, Christian and B{\"u}lthoff, Heinrich H},
title = {{Categorization of natural scenes}},
journal = {ACM Transactions on Applied Perception},
year = {2007},
volume = {4},
number = {3},
pages = {19--es},
month = nov
}

@inproceedings{Thomaz:2009uk,
author = {Thomaz, A L and Cakmak, M},
title = {{Learning about objects with human teachers}},
booktitle = {Human-Robot Interaction (HRI), 2009 4th ACM/IEEE International Conference on},
year = {2009},
pages = {15--22}
}

@article{Adler:2010uy,
author = {Adler, R J and Bobrowski, O and Borman, MS and Subag, E},
title = {{Persistent homology for random fields and complexes}},
journal = {ArXiv e- {\ldots}},
year = {2010}
}

@article{Mugan:2007ut,
author = {Mugan, J and Kuipers, Benjamin J},
title = {{Learning Distinctions and Rules in a Continuous World Through Active Exploration}},
year = {2007}
}

@inproceedings{Deng:2013jk,
author = {Deng, Jia and Krause, J and Fei-Fei, Li},
title = {{Fine-Grained Crowdsourcing for Fine-Grained Recognition}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on},
year = {2013},
pages = {580--587}
}

@article{HAVE:2011ts,
author = {Vidal, Ren{\'e}},
title = {{Subspace Clustering}},
year = {2011}
}

@article{Sommer:2014vb,
author = {Sommer, N and Li, M and Billard, A},
title = {{Bimanual Compliant Tactile Exploration for Grasping Unknown Objects}},
journal = {IEEE International Conference on {\ldots}},
year = {2014}
}

@article{Long:2014um,
author = {Long, Jonathan and Shelhamer, Evan and Darrell, Trevor J},
title = {{Fully Convolutional Networks for Semantic Segmentation}},
journal = {arXiv.org},
year = {2014},
eprint = {1411.4038v2},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = nov,
annote = {to appear in CVPR (2015)}
}

@article{Schaal:2003ic,
author = {Schaal, Stefan and Ijspeert, Auke J and Billard, Aude},
title = {{Computational approaches to motor learning by imitation.}},
journal = {Philosophical transactions of the Royal Society of London. Series B, Biological sciences},
year = {2003},
volume = {358},
number = {1431},
pages = {537--547},
month = mar
}

@inproceedings{Zhang:2012ek,
author = {Zhang, Ziming and Sturgess, P and Sengupta, S and Crook, N and Torr, Philip H S},
title = {{Efficient discriminative learning of parametric nearest neighbor classifiers}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on},
year = {2012},
pages = {2232--2239}
}

@inproceedings{Grimmett:2013io,
author = {Grimmett, H and Paul, R and Triebel, R and Posner, I},
title = {{Knowing when we don't know: Introspective classification for mission-critical decision making}},
booktitle = {Robotics and Automation (ICRA), 2013 IEEE International Conference on},
year = {2013},
pages = {4531--4538}
}

@article{Lowe:2004kp,
author = {Lowe, David G},
title = {{Distinctive Image Features from Scale-Invariant Keypoints}},
journal = {International Journal of Computer Vision},
year = {2004},
volume = {60},
number = {2},
pages = {91--110}
}

@article{Lyubova:2015ec,
author = {Lyubova, Natalia and Ivaldi, Serena and Filliat, David},
title = {{From passive to interactive object learning and recognition through self-identification on a humanoid robot}},
journal = {Autonomous Robots},
year = {2015},
pages = {1--25},
month = jun
}

@article{vanHoof:2014cx,
author = {van Hoof, Herke and Kroemer, Oliver and 0001, Jan Peters},
title = {{Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments.}},
journal = {IEEE Transactions on Robotics ()},
year = {2014},
volume = {30},
number = {5},
pages = {1198--1209}
}

@article{VanGelder:1995wd,
author = {Van Gelder, T and Port, R F},
title = {{Mind as Motion: Explorations in the Dynamics of Cognition - Robert F. Port, Timothy Van Gelder - Google Books}},
journal = {{\ldots} Explorations in the dynamics of cognition},
year = {1995}
}

@article{Leordeanu:2012tu,
author = {Leordeanu, M and Sukthankar, R and Hebert, M},
title = {{Unsupervised Learning for Graph Matching - Springer}},
journal = {International Journal of Computer {\ldots}},
year = {2012}
}

@inproceedings{Zitnick:2013em,
author = {Zitnick, C L and Parikh, D},
title = {{Bringing Semantics into Focus Using Visual Abstraction}},
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on},
year = {2013},
pages = {3009--3016}
}

@article{Lopes:2007bo,
author = {Lopes, Manuel and Santos-Victor, Jos{\'e}},
title = {{A Developmental Roadmap for Learning by Imitation in Robots}},
journal = {IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics)},
year = {2007},
volume = {37},
number = {2},
pages = {308--321},
month = apr
}

@article{Romero:2012uf,
author = {Romero, Javier and Kjellstr{\"o}m, Hedvig and Ek, Carl Henrik and Kragic, Danica},
title = {{Non-Parametric Hand Pose Estimation with Object Context}},
year = {2012},
pages = {1--21},
month = oct,
annote = {<b>First read.</b>

<b>Terms to lookup</b>
Kernel density estimation for modeling conditional distributions,

<b>Review</b>
Gaaah all figures does not have any axises, that actually kind of suxxs. Sorry.




}
}

@article{Titsias:2009vf,
author = {Titsias, Michalis K},
title = {{Variational learning of inducing variables in sparse Gaussian processes}},
journal = {eprintspascal-networkorg},
year = {2009}
}

@article{Pokorny:2012uc,
author = {Pokorny, Florian and Ek, Carl Henrik and Kjellstr{\"o}m, Hedvig},
title = {{Persistent Homology for Learning Densities with Bounded Support}},
journal = {Advances in Neural Information Processing Systems {\ldots}},
year = {2012}
}

@article{Ugur:2011kv,
author = {Ugur, Emre and Oztop, Erhan and Sahin, Erol},
title = {{Going beyond the perception of affordances: Learning how to actualize them through behavioral parameters.}},
journal = {ICRA},
year = {2011},
pages = {4768--4773}
}

@article{Carroll:2005jv,
author = {Carroll, James L and Seppi, Kevin D},
title = {{Task similarity measures for transfer in reinforcement learning task libraries}},
journal = {Carroll, James L},
year = {2005},
volume = {2}
}

@inproceedings{Wang:2014hi,
author = {Wang, Chang and Hindriks, K V and Babuska, R},
title = {{Effective transfer learning of affordances for household robots}},
booktitle = {Development and Learning and Epigenetic Robotics (ICDL-Epirob), 2014 Joint IEEE International Conferences on},
year = {2014},
pages = {469--475},
publisher = {IEEE}
}

@article{Girshick:2013vu,
author = {Girshick, Ross and Donahue, Jeff and Darrell, Trevor J and Malik, Jitendra},
title = {{Rich feature hierarchies for accurate object detection and semantic segmentation}},
journal = {arXiv.org},
year = {2013},
eprint = {1311.2524v5},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = nov,
annote = {Extended version of our CVPR 2014 paper; latest update (v5) includes
  results using deeper networks (see Appendix G. Changelog)}
}

@article{Xu:2015ut,
author = {Xu, Kelvin and Ba, Jimmy and Kiros, Ryan and Cho, Kyunghyun and Courville, Aaron and Salakhutdinov, Ruslan and Zemel, Richard and Bengio, Yoshua},
title = {{Show, Attend and Tell: Neural Image Caption Generation with Visual Attention}},
journal = {arXiv.org},
year = {2015},
eprint = {1502.03044v2},
eprinttype = {arxiv},
eprintclass = {cs.LG},
month = feb
}

@article{Awaad:2013uc,
author = {Awaad, I and Kraetzschmar, G K},
title = {{Affordance-based reasoning in robot task planning}},
journal = {Planning and robotics ( {\ldots}},
year = {2013}
}

@article{Razavian:2014fl,
author = {Razavian, Ali Sharif and Azizpour, Hossein and Sullivan, Josephine and Carlsson, Stefan},
title = {{CNN Features Off-the-Shelf: An Astounding Baseline for Recognition.}},
journal = {CVPR Workshops},
year = {2014},
pages = {512--519}
}

@article{Gibson:1978we,
author = {Gibson, James J},
title = {{The Ecological Approach to the Visual Perception of Pictures}},
journal = {Leonardo},
year = {1978},
volume = {11},
number = {3},
pages = {227--235},
month = jul
}

@inproceedings{Chang:2008hr,
author = {Chang, L Y and Zeglin, G J and Pollard, N S},
title = {{Preparatory object rotation as a human-inspired grasping strategy}},
booktitle = {Humanoid Robots, 2008. Humanoids 2008. 8th IEEE-RAS International Conference on},
year = {2008},
pages = {527--534}
}

@article{Provost:2004wr,
author = {Provost, J and Kuipers, Benjamin J and Miikkulainen, R},
title = {{Self-organizing perceptual and temporal abstraction for robot reinforcement learning}},
journal = {AAAI-04 workshop on learning and {\ldots}},
year = {2004}
}

@article{Mao:2014vc,
author = {Mao, Junhua and Xu, Wei and Yang, Yi and Wang, Jiang and Yuille, Alan L},
title = {{Explain Images with Multimodal Recurrent Neural Networks}},
journal = {arXiv.org},
year = {2014},
eprint = {1410.1090v1},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = oct
}

@article{Zia:wd,
author = {Zia, M Z and Stark, M and Schindler, K},
title = {{Explicit Occlusion Modeling for 3D Object Class Representations}},
journal = {cv-foundation.org
}
}

@inproceedings{Huebner:2008ia,
author = {Huebner, Kai and Ruthotto, S and Kragic, Danica},
title = {{Minimum volume bounding box decomposition for shape approximation in robot grasping}},
booktitle = {2008 IEEE International Conference on Robotics and Automation},
year = {2008},
pages = {1628--1633}
}

@article{Schwander:tz,
author = {Schwander, Olivier and Nielsen, Frank},
title = {{Model Centroids for the Simplification of Kernel Density Estimators}},
journal = {lix.polytechnique.fr}
}

@article{Heckerman:5n_Zf8iM,
author = {Heckerman, David},
title = {{Likelihood and Parameter Priors for Bayesian Networks}}
}

@article{Zeiler:2013ws,
author = {Zeiler, Matthew D and Fergus, Rob},
title = {{Visualizing and Understanding Convolutional Networks}},
journal = {arXiv.org},
year = {2013},
month = nov
}

@article{Blumer:1989cd,
author = {Blumer, Anselm and Ehrenfeucht, A and Haussler, David and Warmuth, Manfred K},
title = {{Learnability and the Vapnik-Chervonenkis dimension}},
journal = {Journal of the ACM (JACM},
year = {1989},
volume = {36},
number = {4},
month = oct
}

@article{Blumer:1987vk,
author = {Blumer, Anselm and Ehrenfeucht, A and Haussler, David},
title = {{Occam's Razor}},
journal = {Information processing {\ldots}},
year = {1987}
}

@incollection{Scholkopf:2005jm,
author = {Sch{\"o}lkopf, Bernhard and Smola, Alexander and M{\"u}ller, Klaus-Robert},
title = {{Kernel principal component analysis}},
booktitle = {Artificial Neural Networks---ICANN'97},
year = {2005},
pages = {583--588},
publisher = {Springer Berlin Heidelberg},
address = {Berlin, Heidelberg},
month = jun
}

@inproceedings{Griffith:2010kw,
author = {Griffith, S and Sinapov, J and Sukhoy, V and Stoytchev, A},
title = {{How to separate containers from non-containers? a behavior-grounded approach to acoustic object categorization}},
booktitle = {Robotics and Automation (ICRA), 2010 IEEE International Conference on},
year = {2010},
pages = {1852--1859}
}

@article{Hansen:2007vi,
author = {Hansen, E A},
title = {{Indefinite-horizon POMDPs with action-based termination}},
journal = {{\ldots} OF THE NATIONAL CONFERENCE ON ARTIFICIAL {\ldots}},
year = {2007}
}

@inproceedings{Konidaris:2006jl,
author = {Konidaris, George and Barto, Andrew G},
title = {{Autonomous shaping: knowledge transfer in reinforcement learning}},
booktitle = {ICML '06: Proceedings of the 23rd international conference on Machine learning},
year = {2006},
publisher = { ACM},
month = jun
}

@article{Wessel:2008ua,
author = {Wessel, R and Baranowski, R and Klein, R},
title = {{Vision, Modeling, and Visualization 2008: Proceedings, October 8-10, 2008 ... - Google Books}},
journal = {VMV},
year = {2008}
}

@article{Modayil:2008it,
author = {Modayil, Joseph and Kuipers, Benjamin J},
title = {{The initial development of object knowledge by a learning robot}},
journal = {Robotics and Autonomous Systems},
year = {2008},
volume = {56},
number = {11},
pages = {879--890},
month = nov
}

@article{Argyros:2004tv,
author = {Argyros, Antonis A and Lourakis, Manolis I A},
title = {{Real-Time Tracking of Multiple Skin-Colored Objects with a Possibly Moving Camera - Springer}},
journal = {Computer Vision-ECCV 2004},
year = {2004},
annote = {<b>Second read.</b>

<b>Terms to look-up</b>
Hysteresis thresholding

<b>Review</b> 
Real-time tracking of hands using skin color feature. 

Skin color detection is done via  probabilistic thresholding. The probabilities are calculated from the image via some notion of skincolor in the image. The online probabilities are a weighted sum of the off-line trained images and the previous image frame statistics to let it be less sensitive to illumination and image quality etc.

The tracking of the hands is done via a certain kind of hypothesis / truth matching. The hypothesizes are inherited from the previous frame and then made to be matched with the current frame. Matching is done corresponding to a specific ruleset matching pixels to skin color blobs. Hypothesizes are thrown away if they don't match the reality.

The testing of the method is performed on a 3825 frames long clip of some dude waving his hands really really fast{\ldots} The labeling is done correctly in every frame but they don't give any more insight to exactly how good it is in general i.e. thin experiment section, but seemingly promising.



}
}

@article{Kolmogorov:2004he,
author = {Kolmogorov, V and Zabin, R},
title = {{What energy functions can be minimized via graph cuts?}},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
year = {2004},
volume = {26},
number = {2},
pages = {147--159}
}

@book{Vapnik:1998uq,
author = {Vapnik, Vladimir Naumovich},
title = {{Statistical learning theory}},
publisher = {Wiley-Interscience},
year = {1998},
month = sep
}

@article{Thrun:2001bi,
author = {Thrun, Sebastian and Fox, Dieter and Burgard, Wolfram and Dellaert, Frank},
title = {{Robust Monte Carlo localization for mobile robots}},
journal = {Artificial Intelligence Review},
year = {2001},
volume = {128},
number = {1-2},
pages = {99--141},
month = may
}

@article{Bicchi:2000wr,
author = {Bicchi, A and Kumar, V},
title = {{Robotic Grasping and Contact: A Review}},
journal = {Robotics {\&} Automation {\ldots}},
year = {2000}
}

@article{Berenson:2011hi,
author = {Berenson, D and Srinivasa, S and Kuffner, J},
title = {{Task Space Regions: A framework for pose-constrained manipulation planning}},
journal = {The International Journal of Robotics Research},
year = {2011},
volume = {30},
number = {12},
pages = {1435--1460},
month = oct
}

@article{Garcia:2012kg,
author = {Garcia, Carlos},
title = {{A simple procedure for the comparison of covariance matrices}},
journal = {BMC Evolutionary Biology},
year = {2012},
volume = {12},
number = {1},
pages = {222}
}

@article{Duchenne:2011cz,
author = {Duchenne, O and Bach, F and Kweon, In-So and Ponce, J},
title = {{A Tensor-Based Algorithm for High-Order Graph Matching}},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
year = {2011},
volume = {33},
number = {12},
pages = {2383--2395}
}

@article{Nielsen:2009ct,
author = {Nielsen, Frank and Nock, Richard},
title = {{Approximating Smallest Enclosing Balls With Applications To Machine Learning}},
journal = {dx.doi.org},
year = {2009},
volume = {19},
number = {05},
pages = {389--414},
month = oct
}

@inproceedings{Sweeney:2007cn,
author = {Sweeney, J D and Grupen, R},
title = {{A model of shared grasp affordances from demonstration}},
booktitle = {Humanoid Robots, 2007 7th IEEE-RAS International Conference on},
year = {2007},
pages = {27--35}
}

@article{Grunwald:2004vi,
author = {Grunwald, Peter},
title = {{A tutorial introduction to the minimum description length principle}},
journal = {arXiv.org},
year = {2004},
eprint = {math/0406077v1},
eprinttype = {arxiv},
eprintclass = {math.ST},
month = jun
}

@techreport{Kruger:TMc75Po8,
author = {Kr{\"u}ger, Norbert and Piater, Justus and Kragic, Danica and Eklundh, J-O},
title = {{Formal definition of object action complexes and examples at different levels of the process hierarchy}}
}

@article{Vinyals:2014wm,
author = {Vinyals, Oriol and Toshev, Alexander and Bengio, Samy and Erhan, Dumitru},
title = {{Show and Tell: A Neural Image Caption Generator}},
journal = {arXiv.org},
year = {2014},
eprint = {1411.4555v2},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = nov
}

@article{Venugopalan:2014wc,
author = {Venugopalan, Subhashini and Xu, Huijuan and Donahue, Jeff and Rohrbach, Marcus and Mooney, Raymond and Saenko, Kate},
title = {{Translating Videos to Natural Language Using Deep Recurrent Neural Networks}},
journal = {arXiv.org},
year = {2014},
eprint = {1412.4729v2},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = dec,
annote = {Corrected minor typos}
}

@article{Chen:2014wo,
author = {Chen, Xinlei and Zitnick, C Lawrence},
title = {{Learning a Recurrent Visual Representation for Image Caption Generation}},
journal = {arXiv.org},
year = {2014},
eprint = {1411.5654v1},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = nov
}

@article{Csurka:2004ud,
author = {Csurka, G and Dance, C and Fan, L},
title = {{Visual categorization with bags of keypoints}},
journal = {Workshop on statistical {\ldots}},
year = {2004}
}

@article{Fang:2014wk,
author = {Fang, Hao and Gupta, Saurabh and Iandola, Forrest and Srivastava, Rupesh and Deng, Li and Doll{\'a}r, Piotr and Gao, Jianfeng and He, Xiaodong and Mitchell, Margaret and Platt, John C and Zitnick, C Lawrence and Zweig, Geoffrey},
title = {{From Captions to Visual Concepts and Back}},
journal = {arXiv.org},
year = {2014},
eprint = {1411.4952v3},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = nov,
annote = {version corresponding to CVPR15 paper}
}

@article{Schroff:2015wo,
author = {Schroff, Florian and Kalenichenko, Dmitry and Philbin, James},
title = {{FaceNet: A Unified Embedding for Face Recognition and Clustering}},
journal = {arXiv.org},
year = {2015},
eprint = {1503.03832v1},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = mar,
annote = {To appear in Proceedings of the IEEE Computer Society Conference on
  Computer Vision and Pattern Recognition 2015}
}

@inproceedings{Nakamura:2007ct,
author = {Nakamura, T and Nagai, Takayuki and Iwahashi, N},
title = {{Multimodal object categorization by a robot}},
booktitle = {Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on},
year = {2007},
pages = {2415--2420}
}

@article{Chen:2014tj,
author = {Chen, Liang-Chieh and Papandreou, George and Kokkinos, Iasonas and Murphy, Kevin and Yuille, Alan L},
title = {{Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs}},
journal = {arXiv.org},
year = {2014},
eprint = {1412.7062v3},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = dec,
annote = {Camera ready for ICLR 2015. Best model attains 71.6% on PASCAL VOC
  2012 test set without annotations from other datasets}
}

@inproceedings{Davis:2009jg,
author = {Davis, Jesse and Domingos, Pedro},
title = {{Deep transfer via second-order Markov logic}},
booktitle = {ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning},
year = {2009},
publisher = { ACM},
month = jun
}

@article{Bahdanau:2014vz,
author = {Bahdanau, Dzmitry and Cho, Kyunghyun and Bengio, Yoshua},
title = {{Neural Machine Translation by Jointly Learning to Align and Translate}},
journal = {arXiv.org},
year = {2014},
eprint = {1409.0473v5},
eprinttype = {arxiv},
eprintclass = {cs.CL},
month = sep,
annote = {Accepted at ICLR 2015 as oral presentation}
}

@article{Xu:2009um,
author = {Xu, C and Kuipers, Benjamin J},
title = {{Construction of the Object Semantic Hierarchy}},
journal = {sensors},
year = {2009}
}

@article{Girshick:2014ut,
author = {Girshick, Ross and Iandola, Forrest and Darrell, Trevor J and Malik, Jitendra},
title = {{Deformable Part Models are Convolutional Neural Networks}},
journal = {arXiv.org},
year = {2014},
eprint = {1409.5403v2},
eprinttype = {arxiv},
eprintclass = {cs.CV},
month = sep
}

@article{Ek:2008bl,
author = {Ek, Carl Henrik and Torr, Philip H S and Lawrence, Neil D},
title = {{Gaussian Process Latent Variable Models For Human Pose Estimation}},
journal = {Machine learning for multimodal interaction},
year = {2008},
volume = {4892},
number = {Chapter 12},
pages = {132--143},
annote = {<b>1.5 Read.

Terms to lookup</b>
Back constrained GPLVM



<b>Review</b>
Pose estimation using regression, back constrained GPLVMs and so on. Need a better grip on this paper.}
}

@inproceedings{Wu:2009fs,
author = {Wu, Jianxin and Rehg, J M},
title = {{Beyond the Euclidean distance: Creating effective visual codebooks using the Histogram Intersection Kernel}},
booktitle = {Computer Vision, 2009 IEEE 12th International Conference on},
year = {2009},
pages = {630--637}
}

@article{Damianou:2014wn,
author = {Damianou, Andreas C and Titsias, Michalis K and Lawrence, Neil D},
title = {{Variational Inference for Uncertainty on the Inputs of Gaussian Process Models}},
journal = {arXiv.org},
year = {2014},
eprint = {1409.2287v1},
eprinttype = {arxiv},
eprintclass = {stat.ML},
month = sep,
annote = {51 pages (of which 10 is Appendix), 19 figures}
}