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Proceedings Paper

Object-oriented video structuring via hidden Markov models
Author(s): Yi Ding; Laiyao Fan
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Paper Abstract

In this paper, we propose a novel statistical method for video analysis and object-oriented structured video representation. Although the existing shot-based approaches facilitate our access to video than the raw video data do, they are still not effective for the semantic level video browsing and retrieval. To represent video structure on semantic levels, the proposed method employs an extended hidden Markov model trained by EM algorithm in order to explore the meaningful objects and the important video structures. According to the principles of the proposed method, important objects and video structure with the consideration of short term statistic as well as long term recurrence can be captured and several interesting video analysis tasks can also be performed. Finally, experiments based on several different videos validate the effectiveness of the proposed approach.

Paper Details

Date Published: 31 July 2006
PDF: 7 pages
Proc. SPIE 5960, Visual Communications and Image Processing 2005, 596019 (31 July 2006); doi: 10.1117/12.631558
Show Author Affiliations
Yi Ding, Xidian Univ. (China)
Laiyao Fan, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 5960:
Visual Communications and Image Processing 2005
Shipeng Li; Fernando Pereira; Heung-Yeung Shum; Andrew G. Tescher, Editor(s)

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