Research on Shot Detection Algorithm of Self-adaptive Dual Thresholds Based on Multi-feature Fusion

Abstract

The shot is basic physical unit of video sequence, which is a collection of several consecutive frames in time and space that is captured by a camera. Shot boundary detection is the structural basis of video retrieval, the performance of detection algorithm will directly affect the efficiency of video retrieval. By describing and analyzing advantages and disadvantages of existing algorithms, this paper proposes a shot detection algorithm of self-adaptive dual thresholds based on multi-feature fusion. Firstly, frame difference is calculated by combining HSV color feature and LBP texture feature in the image that is non-uniformly divided into several blocks. Secondly, frame difference is compared with two self-adaptive thresholds to detect shot boundary. Finally, video is segmented some independent shots. Experiment analysis shows that this algorithm can’t only extract features that reflect main contents of video images, but also effectively detect abrupt shots and gradual shots. It reduces the number of false detection and miss detection, therefore, it has higher recall and precision than existing shot boundary detection algorithms. To a certain extent, this algorithm improves the efficiency of shot boundary detection.