A divide-and-rule scheme for shot boundary detection based on SIFT

Shot boundary detection is an important fundamental process toward automatic video indexing, retrieval, editing, etc. After a critical review of most approaches seeking to solve this problem, we propose a novel shot boundary detection. To improve the performance of the algorithm and reduce the computational cost, frames that are clearly not shot boundaries are first removed from the original video. After that, a novel SIFT keypoint matching algorithm based on SVM is proposed, which is used to capture the changing statistics of different kinds of shot transitions so as to identify, not only abrupt transitions, but also gradual transitions(fade, dissolve, wipe) accordingly. At last, our system use different algorithms for different kinds of shot transitions to help us to get a better solution for shot boundary detection problem. Numerical experiments in the evaluation of TRECVID and a variety of film videos demonstrate that our method is capable of accurately detecting shot transitions, and could greatly reduce the computational cost.