a general framework for automatic on-line replay detection in sports video
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.
replay detection bayesian network motion vector reliability sports video analysis