Abstract
We present a statistical approach for parsing football video structures. Based on video production conventions, a new generic structure called ‘attack’ is identified, which is an equivalent of scene in other video domains. We define four video segments to construct it, namely play, focus, replay and break. Two middle level visual features, play field ratio and zoom size, are also computed. The detection process includes a two-pass classifier, a combination of Gaussian Mixture Model and Hidden Markov Models. A general suffix tree is introduced to identify and organize ‘attack’. In experiments, video structure classification accuracy of about 86% is achieved on broadcasting World Cup 2002 video data.
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Ren, R., Jose, J.M. (2005). Football Video Segmentation Based on Video Production Strategy. In: Losada, D.E., Fernández-Luna, J.M. (eds) Advances in Information Retrieval. ECIR 2005. Lecture Notes in Computer Science, vol 3408. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31865-1_31
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DOI: https://doi.org/10.1007/978-3-540-31865-1_31
Publisher Name: Springer, Berlin, Heidelberg
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