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.