Shot Segmentation for Binocular Stereoscopic Video Based on Spatial–Temporal Feature Clustering

Abstract

Shot segmentation is the key to content-based analysis, index and retrieval of binocular stereoscopic video. To solve the problem of low accuracy of stereoscopic video shot segmentation in which the segmentation method of 2D video is used to segment monocular video sequence, and the disadvantages of some stereoscopic video shot segmentation methods, a shot segmentation method for binocular stereoscopic video based on spatial---temporal feature clustering (STFC) is proposed. In the method, the features of color and brightness of left video frames in temporal domain as well as the depth feature acquired by matching of left and right frames in spatial domain is extracted. The feature differences between frames are calculated and quantified. Then the clustering of feature differences in three-dimensional space is executed, and the optimization and iteration of the classes are implemented to achieve the division of shot boundary. The experimental results show that the proposed method can effectively solve the problems of error and omission, especially the inaccuracy of smooth shot detection in binocular stereo video shot segmentation when compared with the latest existing algorithm. The higher accuracy of segmentation can be achieved.