A general framework for automatic on-line replay detection in sports video

Authors:
Bo Han;Yan Yan;Zhenghua Chen;Chang Liu;Weiguo Wu
Affiliations:
Sony China Research Laboratory, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Sony China Research Laboratory, Beijing, China
Venue:
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Year:
2009

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Abstract

Replay detection is a pivotal step for sports video highlight extraction, which is a very promising application of multimedia analysis. In this paper, a general framework, which is based on a Bayesian network, is proposed to make full use of the multiple clues, including shot structure, gradual transition pattern, slow-motion, and sports scene. A novel algorithm based on motion vector reliability classification is proposed to analyze the gradual transition patterns, so that the replay detector can meet the requirements of automatic on-line applications. This is the first integrated general replay detection framework proposed in the literature. Extensive experiments on diversified sports games have proven the scheme efficient, accurate and robust.