Gaussian Mixture Models for Video Recognition

1. Build a global GMM based on SIFT features from training videos
2. Build a specialised GMM for each video clip
3. Measure video-video distance using a formula induced from Kullback–Leibler divergence

Reference

[1] X. Zhou, X. Zhuang, S. Yan, S.-F. Chang, M. Hasegawa-Johnson, and T. S. Huang, “Sift-bag kernel for video event analysis,” in Proceedings of the 16th ACM international conference on Multimedia. ACM, 2008, pp. 229–238.