NDLI: Group action recognition in soccer videos

Content Provider	IEEE Xplore Digital Library
Author	Yu Kong Xiaoqin Zhang Qingdi Wei Weiming Hu Yunde Jia
Copyright Year	2008
Description	Author affiliation: Sch. of Comput. Sci., Beijing Inst. of Technol., Beijing, China (Yu Kong; Yunde Jia) \|\| Nat. Lab. of Pattern Recognition, Inst. of Autom., Beijing, China (Xiaoqin Zhang; Qingdi Wei; Weiming Hu)
Abstract	Group action recognition in soccer videos is a challenging problem due to the difficulties of group action representation and camera motion estimation. This paper presents a novel approach for recognizing group action with a moving camera. In our approach, ego-motion is estimated by the Kanade-Lucas-Tomasi feature sets on successive frames. The optical flow is then computed on compensated frames. Due to the inaccurate ego-motion estimation, the optical flow can not reflect accurate motion of objects. In this paper, we propose a new motion descriptor which treats the optical flow as spatial patterns and extracts accurate global motion from the noisy optical flow. The latent-dynamic conditional random field model is employed to recognize group action. Experimental results show that our approach is promising.
Starting Page	1
Ending Page	4
File Size	223045
Page Count	4
File Format	PDF
ISBN	9781424421749
ISSN	10514651
DOI	10.1109/ICPR.2008.4761001
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Videos Image motion analysis Cameras Optical computing Optical noise Pattern recognition Laboratories Motion estimation Event detection Surveillance
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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