A statistical framework for replay detection in soccer video

A novel statistical framework for replay detection is presented in this paper. Unlike current methods, the proposed framework exploits both inherent characters and transition relations of replay and non-replay scenes based on annotation of the video, which realizes segments and classifies video stream into replay and non-replay shots simultaneously. After annotation, the detected replay segment is further verified and its boundaries are adjusted to get more accurate replay segment considering probability distribution of lengths of replay and non-replay shots. Experimental results on soccer video are promising, demonstrating the effectiveness of the proposed framework.

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