A motion-based scene tree for compressed video content management

Abstract

This paper describes a fully automatic content-based approach for browsing and retrieval of MPEG-2 compressed video. The first step of the approach is the detection of shot boundaries based on motion vectors available from the compressed video stream. The next step involves the construction of a scene tree from the shots obtained earlier. The scene tree is shown to capture some semantic information as well as provide a construct for hierarchical browsing of compressed videos. Finally, we build a new model for video similarity based on global as well as local motion associated with each node in the scene tree. To this end, we propose new approaches to camera motion and object motion estimation. The experimental results demonstrate that the integration of the above techniques results in an efficient framework for browsing and searching large video databases.