A Robust Multi-Feature Cut Detection Algorithm for Video Segmentation

Video segmentation is the first task in almost all video analysis applications. It consists in identifying the boundaries of the meaningful video units (shots). Without a doubt, cuts are the most common among production effects that characterize the shot boundaries. In this paper we propose an algorithm for cut detection exploiting an innovative, robust frame difference measure. The measure is based on a combination of different visual features. To improve the precision of the cut detection algorithm, a temporal pattern analysis model, and a flashes removal are also proposed. Experimental results to prove the effectiveness of the proposed measure coupled with the temporal pattern analysis model on very heterogeneous and complex sets of videos are critically reported.