by: Alex Chang
Scalable Image Vocabulary Tree Implementing [1] using Stanford Mobile Visual Search imageset [2] as test and training dataset
[1] implementation details:
(a) Keypoint detection (b) Keypoint description with rotation and scale in-variance (c) Building and using the vocabulary tree (i.e. quantization) (d) Hierarchical scoring (e) Retrieval
STEP 1: For a test image, retrieve top 10 matches (DVD cover images from the database) returned via the implemented approach.
Then... using RANSAC: STEP 2: Compute a homography with your implementation from above for each retrieved DVD cover image and the test image. STEP 3: Find the DVD cover image from (4) with the highest number of inliers. Plot the test image with the localized DVD cover as well as the best retrieved DVD cover
Reference:
[1] Nister, Stewenius, Scalable Recognition with a Vocabulary Tree, CVPR 2006, http://www-inst.eecs.berkeley.edu/~cs294-6/fa06/papers/nister_stewenius_cvpr2006.pdf