Data indexing for video shot mining based on optical flow

Summarizing and understanding video shot based on their contents is an important research topic in multimedia data mining. This paper presents an efficient algorithm based on optical flow field to mine the motion data contained in a given video shot. Two features called magnitude of motion pixel and direction of motion pixel are constructed respectively and adopted to split the video shot into some categories automatically. The corresponding indexical structure is extracted from each category and directly applied to motion-based queries. A test system has been developed to prove the validity of our algorithm. The experimental results show that the algorithm performs well and will play an important role in content-based video shot retrieval.