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

Ren, Jinchang and Chen, Juan and Jiang, Jianmin and Ipson, Stan S.; Huang, De-Shuang and Wunsch II, Donald C. and Levine, Daniel S. and Jo, Kang-Hyun, eds. (2008) Knowledge-supported Segmentation and Semantic Contents Extraction from MPEG Videos for Highlight-based Annotation, Indexing and Retrieval. In: Advanced intelligent computing theories and applications. Lecture Notes in Computer Science . Springer, CHN, pp. 258-265. ISBN 9783540874409 (https://doi.org/10.1007/978-3-540-87442-3)

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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 skindetection. 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.

ORCID iDs

Ren, Jinchang ORCID logoORCID: https://orcid.org/0000-0001-6116-3194, Chen, Juan, Jiang, Jianmin and Ipson, Stan S.; Huang, De-Shuang, Wunsch II, Donald C., Levine, Daniel S. and Jo, Kang-Hyun
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