Figure 1

This flow chart summarizes our approach: given a set of video sequences, we start with spatial-temporal interest points extraction. The extracted interest points from each sequence are then matched pairwise using Hungarian method with shape context features incorporated. The matching scores encoding the similarities between any two features are then refined using link PageRank and structure similarity to further enhance distinctive features while suppress noisy ones. Later, the two resulting refined scores are then jointly fed into a clustering algorithm.