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- W1996979501 abstract "We propose a fully automatic and flexible framework for analysis and summarization of tennis broadcast video sequences, using visual features and specific game-context knowledge. Our framework can analyze a tennis video sequence at three levels, which provides a broad range of different analysis results. The proposed framework includes novel pixel-level and object-level tennis video processing algorithms, such as a moving-player detection taking both the color and the court (playing-field) information into account, and a player-position tracking algorithm based on a <i>3-D</i> camera model. Additionally, we employ scene-level models for detecting events, like service, base-line rally and net-approach, based on a number <i>real-world</i> visual features. The system can summarize three forms of information: (1) all court-view playing frames in a game, (2) the moving trajectory and real-speed of each player, as well as relative position between the player and the court, (3) the semantic event segments in a game. The proposed framework is flexible in choosing the level of analysis that is desired. It is effective because the framework makes use of several visual cues obtained from the <i>real-world</i> domain to model important events like service, thereby increasing the accuracy of the scene-level analysis. The paper presents attractive experimental results highlighting the system efficiency and analysis capabilities." @default.
- W1996979501 created "2016-06-24" @default.
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- W1996979501 date "2006-01-15" @default.
- W1996979501 modified "2023-10-10" @default.
- W1996979501 title "Multilevel analysis of sports video sequences" @default.
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- W1996979501 doi "https://doi.org/10.1117/12.648849" @default.
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