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ICMCS
2006
IEEE

Extracting Story Units in Sports Video Based on Unsupervised Video Scene Clustering

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Extracting Story Units in Sports Video Based on Unsupervised Video Scene Clustering
Many sports videos such as archery, diving and tennis have repetitive structure patterns. They are reliable clues to generate highlights, summarization and automatic annotation. In this paper, we present a novel approach to analyze these structure patterns in sports video to extract story units. First, an unsupervised scene clustering method for sports video is adopted to automatically categorize the video shots into several disparate scenes. Then, the clustering results are modeled by a transition matrix. Finally, the key scene shots are detected to analyze the structure patterns and extract the story units. Experimental results on several types of broadcast sports video demonstrate that our approach is effective.
Chunxi Liu, Qingming Huang, Shuqiang Jiang, Weigan
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where ICMCS
Authors Chunxi Liu, Qingming Huang, Shuqiang Jiang, Weigang Zhang
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