Visual cognitive mechanism guided video shot segmentation

Abstract

Shot segmentation of video sequences is one of the key technologies in video information processing, especially video retrieval. Traditional shot segmentation methods have low detection rate for the gradient shot and the abrupt shot, especially in a single scene. To deal with this problem, this paper proposes a video segmentation method based on visual cognition mechanism. This method proposes a block granularity color histogram to strengthen the visual salient area, and a highlight measure to describe the difference between the front and back frames. This brings great improvements to the accuracy of detecting shot switching in a single scene. In addition, based on the brightness visual perception in video, the difference between adjacent multi-frames in the sliding window is used to capture the brightness change for the gradient shots. Comparing with traditional methods, the proposed algorithm achieves better segmentation effect and has higher precision and recall rate.