A novel shot detection algorithm based on clustering

Shot boundary detection has attracted much more research interesting in recent years. This paper present a novel shot boundary detection algorithm based on K-means clustering. At first the feature of color is extracted, the dissimilarity of video frames is defined .Then the video frames are divided into several different sub-clusters through performing K-means clustering. It can detect cut and gradual shot by the adaptive double threshold of different sub-clusters. The efficiency of the proposed algorithm is extensively tested on movie, news and other videos. The experiments results indicate the method had a high accurate rate in both cut shot detection and gradual shot detection.