An efficient method for scene cut detection

Abstract In many applications such as video browsing, indexing of relevant scenes in a video sequence is important for their efficient retrieval. Such indexing is most commonly done by identifying scene cuts which represent the boundary between video shots. Scene cut detection involves the identification of frames at which the content of the scene is significantly different from that of the previously retained frames. This requires computing an appropriate metric that characterizes the change in video content between two frames and a threshold to determine whether the change is large enough for the frame to be defined as a scene cut frame. In this paper, we propose a novel method to detect scene cuts adaptively using a difference metric based on the color histograms of successive frames of a video sequence. An entropic thresholding method is used to obtain the threshold automatically for identifying scene cuts. We further apply a refinement procedure to remove false detection. Experimental results are presented to illustrate the good performance of the method.