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Knowledge-supported segmentation and semantic contents extraction from MPEG videos for highlight-based annotation, indexing and retrieval

Main information
Automatic recognition of highlights from videos is a fundamental and challenging problem for content-based indexing and retrieval applications. In this paper, we propose techniques to solve this problem by using knowledge supported extraction of semantic contents, and compressed-domain processing is employed for efficiency. Firstly, video shots are detected by using know-ledge-supported rules. Then, human objects are detected via statistical skin de-tection. Meanwhile, camera motion like zoom in is identified. Finally, highlights of zooming in human objects are extracted and used for annotation, indexing and retrieval of the whole videos. Results from large data of test videos have demonstrated the accuracy and robustness of the proposed techniques. 
No referenced Knowhow defined
WP5: Detection, Extraction and Annotation of Knowledge. 
School of Informatics University of Bradford  Jianmin Jiang, Jinchang Ren 
2008-09-12 11:55  Request for more detail


Access and Use Rights
For educational purposes only - if public document.  For educational purposes only - if public document. 


Protection Status
Copyright School of Informatics, University of Bradford.  Patent Protection not sought. 
Licensing Protection not sought.  Utility Model Protection not sought. 
 
Springer LNCS 5226, pp. 258-265, ISBN 978-3-540-87440-9, 2008. http://www.springerlink.com/content/x280vukw44g54552/ 
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