10 January 2003 Automatic Soccer Video Analysis and Summarization
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Abstract
We propose a fully automatic and computationally efficient framework for analysis and summarization of soccer videos using cinematic and object-based features. The proposed framework includes some novel low-level soccer video processing algorithms, such as dominant color region detection, robust shot boundary detection, and shot classification, as well as some higher-level algorithms for goal detection, referee detection, and penalty-box detection. The system can output three types of summaries: i) all slow-motion segments in a game, ii) all goals in a game, and iii) slow-motion segments classified according to object-based features. The first two types of summaries are based on cinematic features only for speedy processing, while the summaries of the last type contain higher-level semantics. The proposed framework is efficient, effective, and robust for soccer video processing. It is efficient in the sense that there is no need to compute object-based features when cinematic features are sufficient for the detection of certain events, e.g. goals in soccer. It is effective in the sense that the framework can also employ object-based features when needed to increase accuracy (at the expense of more computation). The efficiency, effectiveness, and the robustness of the proposed framework are demonstrated over a large data set, consisting of more than 13 hours of soccer video, captured at different countries and conditions.
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Ahmet Ekin, Ahmet Ekin, A. Murat Tekalp, A. Murat Tekalp, } "Automatic Soccer Video Analysis and Summarization", Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); doi: 10.1117/12.476238; https://doi.org/10.1117/12.476238
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