Recognition of semantic basketball events based on optical flow patterns

Authors

Li Li, Chinese Academy of SciencesFollow
Ying Chen, Beijing Electronic and Science TechnologyFollow
Weiming Hu, Chinese Academy of SciencesFollow
Wanqing Li, University of WollongongFollow
Xiaoqing Zhang, Chinese Academy of SciencesFollow

RIS ID

32118

Publication Details

Li, L., Chen, Y., Hu, W., Li, W. & Zhang, X. (2009). Recognition of semantic basketball events based on optical flow patterns. In G. Bebis (Eds.), Advances in Visual Computing. 5th International Symposium ISVC 2009 Proceedings, Part II (pp. 480-488). Berlin, Germany: Spinger Verlag.

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.