Just to keep myself occupied during some "empty" days between courses, I decided to implement a real time shape recognition system in Matlab. Most of the ideas are based on "Shape Recognition and Pose Estimation for Mobile Augmented Reality" by Nate Hagbi et al. However I didn't implement the pose estimation part since I run out of time. Moreover I encountered some difficulties regarding easier parts of the system (oh yeah image retrieval is not my field per se).
So the idea behind it is simple: locate the most prominent shape (through filtering such as adaptive thresholding), compute its convex hull and perform matching via a bag-of-words approach. Therefore the system firstly needs to be trained. I use SIFT features on a series of projective transformations of the original shape, similar to "Visual Similarity based 3D Shape Retrieval Using Bag-of-Features" by Zhouhui Lian et al. A demonstration is presented below:
