Motion information for video retrieval

In this paper, we propose the use of motion tracks to generate video features, which are applied to perform video retrieval. We simply use the location of the object's center-of-gravity and its velocity across consecutive video frames to from motion flows, which are then recorded and stored in a video database. In the video retrieval phase, we propose the use of n-gram matching strategy to execute the video retrieval task. The retrieval process can be triggered query-by-example. We identify corresponding query and index contents accurately in order to detect “similar” videos. Experiments are carried out on CMU database. An empirical comparison over the state-of-the-art dynamic programming techniques is encouraging and demonstrates the advantage and feasibility of the n-gram method.