Statistical approach to scene change detection

One of the challenging problems in video databases is the organization of video information. Segmenting a video into a number of clips and characterizing each clip has been suggested as one mechanism for organizing video information. This approach requires a suitable method to automatically locate cut points in a video. One way of finding such cut points is to determine the boundaries between consecutive camera shots. In this paper, we address this as a statistical hypothesis testing problem and present three tests to determine cut locations. All the three tests are such that they can be applied directly to the compressed video. This avoids an unnecessary decompression-compression cycle, since it is common to store and transmit digital video in compressed form. As our experimental results indicate, the statistical approach permits accurate detection of scene changes induced through straight as well as optical cuts.