Object segmentation and key-pose based summarization for motion video

This paper proposes a key-pose based video summarization system for a video shot facilitated by using a video object segmentation method. Firstly, we detect the camera motion and extract video objects by a 3D graph-based algorithm. Once the objects are obtained, each of them is represented by a shape descriptor. Secondly, in order to find representative frames which preserve scene content as much accurately as possible, the proposed method calculates difference between pairs of frames based on shape descriptors of objects in the video shot. Finally, key-poses (representative frames) are extracted in a global manner by clustering these shapes. Experimental results on motion video shots show that the proposed method outputs satisfactory summarizations.