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Proceedings Paper

Model-based semantic object extraction for content-based video representation and indexing
Author(s): Jianping Fan; David K. Y. Yau; Mohand-Said Hacid; Ahmed K. Elmagarmid
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Paper Abstract

This paper proposes an integrated system for supporting content-based video retrieval and browsing over networks. An automatic semantic video object extraction technique for providing more compact video representation is developed. The video images are first partitioned into a ste of homogeneous regions with accurate boundaries by integrating the result of color edge detection and region growing procedures. The object seeds, which are the intuitive and representative part of the semantic objects, are detected from these obtained homogeneous image regions. The semantic objects are then generated by a seeded region aggregation or a human interaction procedure. These obtained semantic objects are tracked along the time axis for exploiting their temporal correspondences among frames. Given the semantic video objects represented by a set of visual features, a seeded semantic video content clustering technique is developed for providing more effective video indexing, retrieval and browsing.

Paper Details

Date Published: 1 January 2001
PDF: 13 pages
Proc. SPIE 4315, Storage and Retrieval for Media Databases 2001, (1 January 2001); doi: 10.1117/12.410964
Show Author Affiliations
Jianping Fan, Purdue Univ. (United States)
David K. Y. Yau, Purdue Univ. (United States)
Mohand-Said Hacid, Purdue Univ. (United States)
Ahmed K. Elmagarmid, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 4315:
Storage and Retrieval for Media Databases 2001
Minerva M. Yeung; Chung-Sheng Li; Rainer W. Lienhart, Editor(s)

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