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Automatic story segmentation of news video based on audio-visual features and text information

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4 Author(s)
Ce Wang ; Comput. Sch., Wuhan Univ., China ; Yun Wang ; Hua-Yong Liu ; Yan-Xiang He

In this paper a novel news story automatic segmentation scheme based on audio-visual features and text information is presented. The basic idea is to detect the shot boundaries for news video first, and then the topic-caption frames are identified to get segmentation cues by using text detection algorithm. In the next step, silence clips are detected by using short-time energy and short-time average zero-crossing rate (ZCR) parameters. At last, audio-visual features and text information are integrated to realize automatic story segmentation. On test data with 135, 400 frames, the accuracy rate 85.8% and the recall rate 97.5% are obtained. The experimental results show the approach is valid and robust.

Published in:

Machine Learning and Cybernetics, 2003 International Conference on  (Volume:5 )

Date of Conference:

2-5 Nov. 2003