Discovering Video Shot Categories by Unsupervised Stochastic Graph Partition

Video shots are often treated as the basic elements for retrieving information from videos. In recent years, video shotcategorization has received increasing attention, but most of the methods involve a procedure of supervised learning, i.e., training a multi-class predictor (classifier) on the labeled data. In this paper, we study a general framework to unsupervisedly discover video shot categories. The contributions are three-fold in feature, representation, and inference: (1) A new feat