View article

This paper presents a novel video search system that can provide users with diversified and summarized results automatically. Users frequently confront the dilemmas of specifying conditions for video search because too many or few conditions would lead to either insufficient or redundant results. We solve this problem by introducing novel definitions to explore hidden knowledge inherent in underlying datasets. We demonstrate our methods by implementing a prototype system with real-world surveillance videos.