Recognition of Semantic Basketball Events Based on Optical Flow Patterns

Authors:
Li Li;Ying Chen;Weiming Hu;Wanqing Li;Xiaoqin Zhang
Affiliations:
Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute Department of Basic Sciences, Beijing Electronic and Science Technology, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;University of Wollongong, Sydney, Australia;Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Year:
2009

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Abstract

This paper presents a set of novel features for classifying basketball video clips into semantic events and a simple way to use prior temporal context information to improve the accuracy of classification. Specifically, the feature set consists of a motion descriptor, motion histogram, entropy of the histogram and texture. The motion descriptor is defined based on a set of primitive motion patterns which are derived form optical flow field. The event recognition is achieved by using kernel SVMs and a temporal contextual model. Experimental results have verified the effectiveness of the proposed method.