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Event detection in field sports video using audio-visual features and a support vector machine
Sadlier, David A.; O'Connor, Noel E.
In this paper, we propose a novel audio-visual feature-based framework for event detection in broadcast video of multiple different field sports. Features indicating significant events are selected and robust detectors built. These features are rooted in characteristics common to all genres of field sports. The evidence gathered by the feature detectors is combined by means of a support vector machine, which infers the occurrence of an event based on a model generated during a training phase. The system is tested generically across multiple genres of field sports including soccer, rugby, hockey, and Gaelic football and the results suggest that high event retrieval and content rejection statistics are achievable.
Keyword(s): Multimedia systems; Digital video; Information retrieval; audio-visual systems; digital video broadcasting; feature extraction; sport; support vector machines
Publication Date:
2005
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Sadlier, David A. and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 <https://orcid.org/0000-0002-4033-9135> (2005) Event detection in field sports video using audio-visual features and a support vector machine. IEEE Transactions on Circuits and Systems for Video Technology, 15 (10). pp. 1225-1233. ISSN 1051-8215
Publisher(s): Institute of Electrical and Electronics Engineers
File Format(s): application/pdf
Related Link(s): http://doras.dcu.ie/254/1/ieee_trans_circ_sys_2005.pdf,
http://dx.doi.org/10.1109/TCSVT.2005.854237
First Indexed: 2009-11-05 02:00:27 Last Updated: 2019-02-09 07:04:48