This reposity provides MATLAB implementation of: Model-based hierarchical clustering with Bregman divergences and Fishers mixture model (MBHC-FMM).
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It performs clustering on the 3D directional data using the MBHC-FMM method. It has been applied to cluster image normals (3D unit vectors) to analyze depth image.
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There are three demo files to demonstrate the above mentioned tasks.
Note: Four files: emsamp.m, vsamp.m, unitrand.m and house.m are added here for sampling observations from a specified vMF mixture model. Those files are taken from 'vmfmatlab' code, which is available online.
References:
[1] Hasnat et al., Model-based hierarchical clustering with Bregman divergences and Fishers mixture model: application to depth image analysis. Statistics and Computing, 1-20, 2015. pdf download
[2] Hasnat, M. A., Alata, O., & Trémeau, A. (2014, October). Model based clustering for 3D directional features: application to depth image analysis. In IEEE International Conference on Image Processing (ICIP), pp. 3768-3772, 2014. pdf download
[3] Hasnat et al., Hierarchical 3-D von Mises-Fisher Mixture Model, In 1st Workshop on Divergences and Divergence Learning (ICML-WDDL), 2013. pdf download