A high-performance shot boundary detection algorithm using multiple cues
A central step in content-based video retrieval is the temporal segmentation of video. An application independent approach to video segmentation is to detect temporally contiguous segments without significant content change between successive frames. Each such segment is termed a shot. A high-performance shot boundary detection-based video segmentation algorithm is proposed. The technique uses unsupervised clustering on a multiple feature input space, followed by a heuristic elimination process to detect, with almost perfect accuracy, shot boundaries in the video. With an extremely high accuracy coupled with a very small number of false positives, this algorithm outperforms most of the existing techniques.