Special effect edit detection using VideoTrails: a comparison with existing techniques

Video Segmentation plays an integral role in many multimedia applications such as digital libraries, content management systems, and various other video browsing, indexing, and retrieval systems. Many algorithms for segmentation of video have appeared in the past few years. Most of these algorithms perform well on cuts, but yield poor performance on gradual transitions or special effect edits. A complete video segmentation system must achieve good performance on special effect edit detection also. In this paper, we discuss the performance of our VideoTrails based algorithms with other existing special effect edit detection algorithms in literature. Results from experiments testing for the ability to detect edits from TV programs ranging from commercials to news magazine programs, and also diverse special effect edits introduced by us have been shown.