Key observation selection for effective video synopsis

Millions of video surveillance cameras distribute around the world, and capture tremendous number of video data endlessly. Video browsing by frame is time consuming and inefficient, since needless information is abundant in the raw videos. Video synopsis is an effective way to solve this problem by producing a short video abstraction, while keeping the essential activities of the original video. However, traditional video synopsis only eliminates redundancy in spatial and temporal domain, while neglects redundancy in content domain. However, too many observations will make synopsis video confusing and degrade synopsis efficiency. In this paper, we present a novel video synopsis method based on key observation selection. Key observation selection is conducted for activity to eliminate content redundancy. We have demonstrated the effectiveness of our approach on real surveillance videos.