Knowledge-Supported Segmentation and Semantic Contents Extraction from MPEG Videos for Highlight-Based Annotation, Indexing and Retrieval

  • Authors:

  • Jinchang Ren;Juan Chen;Jianmin Jiang;Stan S. Ipson

  • Affiliations:

  • School of Informatics, University of Bradford, UK BD7 1DP;School of Informatics, University of Bradford, UK BD7 1DP;School of Informatics, University of Bradford, UK BD7 1DP;School of Informatics, University of Bradford, UK BD7 1DP

  • Venue:
  • ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
  • Year:
  • 2008

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Abstract

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 knowledge-supported rules. Then, human objects are detected via statistical skin detection. 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.