Perceived visual motion descriptors from MPEG-2 for content-based HDTV annotation and retrieval

Abstract

Efficient content-based search and retrieval of video databases has become an important industrial and consumer application due to rapid proliferation of compressed digital video data on the Internet and corporate Intranets, and due to the launch of high definition television (HDTV) broadcasts in 1998. We have developed the first HDTV video content management system that automatically analyzes motion occurring in MPEG-2 encoded videos within the compressed domain itself. Our system produces descriptors characterizing the global motion in videos for content retrieval and repurposing applications in a digital television studio. These motion-direction and magnitude based video labels can be directly, incorporated as annotation indexes into a database for querying, or used to construct higher level event descriptions of videos. Results from our ongoing experiments with tens of thousands of frames obtained from several MPEG-1,2 video streams of various genres demonstrate the good performance of our annotation system in terms of motion identification accuracy and computational efficiency.