News story segmentation based on audio-visual features fusion

This paper presents a method for news video story segmentation, which fuses multi-feature including audio and visual. At first, this paper detects the anchorperson shot for news video and determines the beginning of news story, and then detects topic caption between anchorperson shots. In the next step, silence clips in news video are detected using short-time energy and short-time average zero-crossing rate parameters, and then voice features of anchorperson is analyzed. At last, this method fuses multi-feature such as anchorperson shot, topic caption, silence and voice feature to segment news stories. Experimental results show that the approach is valid and avoid the deficiency of detecting news story by a single feature.