Video Retrieval: An Adaptive Novel Feature Based Approach for Movies

Video Retrieval is a field, where many techniques and methods have been proposed and have claimed to perform reliably on the videos like broadcasting of news & sports events. As a movie contains a large amount of visual information varying in random manner, it requires a highly robust algorithm for automatic shot boundary detection as well as retrieval. In this paper, we described a new adaptive approach for shot boundary detection which is able to detect not only abrupt transitions like hard cuts but also special effects like wipes, fades, and dissolves as well in different movies. To partition a movie video into shots and retrieve many metrics were constructed to measure the similarity among video frames based on all the available video features. However, too many features will reduce the efficiency of the shot boundary detection. Therefore, it is necessary to perform feature reduction for every decision. For this purpose we are following a minimum features based algorithm.