A novel motion-based representation for video mining

It is a challenging issue to analyze video content for video mining tasks due to lacking of effective representation of video. As motion is a distinctive feature of video sequence, it is a reasonable and efficient manner to represent video content based on motion. In this paper we proposed a novel motion-based representation for video mining tasks, including a fast dominant motion extraction scheme, called integral template match (ITM), and a set of qualitative and quantitative description schemes. Currently, we applied it to such video mining tasks as shot boundary detection, camera motion segmentation and recognition. The experiments on the test collection of TREC2002 video track have demonstrated the efficiency and robustness of the proposed schemes.