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Using decision-tree to automatically construct learned-heuristics for events classification in sports video

Tjondronegoro, Dian and Chen, Yi-Ping Phoebe 2006, Using decision-tree to automatically construct learned-heuristics for events classification in sports video, in Proceedings of the 2006 IEEE International Conference on Multimedia and Expo, Institute of Electrical and Electronics Engineers, Inc., Piscataway, N.J., pp. 1465-1468.

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Title Using decision-tree to automatically construct learned-heuristics for events classification in sports video
Author(s) Tjondronegoro, Dian
Chen, Yi-Ping Phoebe
Conference name IEEE International Conference on Multimedia and Expo (2006: Toronto, Canada)
Conference location Toronto, Canada
Conference dates 9-12 July 2006
Title of proceedings Proceedings of the 2006 IEEE International Conference on Multimedia and Expo
Editor(s) Guan, Ling
Zhang, Hong-Jiang
Publication date 2006
Conference series International Conference on Multimedia and Expo
Start page 1465
End page 1468
Publisher Institute of Electrical and Electronics Engineers, Inc.
Place of publication Piscataway, N.J.
Summary Automatic events classification is an essential requirement for constructing an effective sports video summary. It has become a well-known theory that the high-level semantics in sport video can be “computationally interpreted” based on the occurrences of specific audio and visual features which can be extracted automatically. State-of-the-art solutions for features-based event classification have only relied on either manual-knowledge based heuristics or machine learning. To bridge the gaps, we have successfully combined the two approaches by using learning-based heuristics. The heuristics are constructed automatically using decision tree while manual supervision is only required to check the features and highlight contained in each training segment. Thus, fully automated construction of classification system for sports video events has been achieved. A comprehensive experiment on 10 hours video dataset, with five full-match soccer and five full-match basketball videos, has demonstrated the effectiveness/robustness of our algorithms.
ISBN 1424403677
9781424403677
Language eng
Field of Research 080610 Information Systems Organisation
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30009748

Document type: Conference Paper
Collections: School of Engineering and Information Technology
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