基于音视频特征的新闻条目自动分割

Automatic Segmentation of News Items Based on Video and Audio Features

Automatic segmentation of news items in a MPEG-2 stream is a significant research topic for implementing an antomatic cataloging system of news video. This paper presents an approach which employes audio and video feature information to automatically segment news items. Combining the analysis techniques of audio and video can overcome the weakness of the approach which only uses the image analysis techniques. This combination makes our appoach more widely adaptable to variable existence situations of news items. The proposed approach detects silence clips in accompanying audio,and integrates with shot segmentation results ,as well as anchor shot detection results ,to determine boundaries between two news items. Experimental results show that the integration of audio and video features is an effective approach to solve the problem of automatic news items segmentation.

Automatic segmentation of news items in a MPEG-2 stream is a significant research topic for implementing an automatic cataloging system of news video. This paper presents an approach which employes audio and video feature information to automatically segment news items. Combining the analysis techniques of audio and video can overcome the weakness of the approach which only uses the image analysis techniques. This combination makes our appoach more widely adaptable to variable existence situations of news items. The proposed approach detects silence clips in accompanying audio,and integrates with shot segmentation results,as well as anchor shot detection results,to determine boundaries between two news items. Experimental results show that the integration of audio and video features is an effective approach to solve the problem of automatic news items segmentation.