ISVC 2009: Advances in Visual Computing pp 480-488 | Cite as
Recognition of Semantic Basketball Events Based on Optical Flow Patterns
Conference paper
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.
Keywords
Video Clip Semantic Event Sport Video Video Event Motion Descriptor
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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