Automatic Classification of Tennis Video for High-level Content-based Retrieval
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Video Annotation for Content-based Retrieval using Human Behavior Analysis and Domain Knowledge
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
An intelligent strategy for the automatic detection of highlights in tennis video recordings
Expert Systems with Applications: An International Journal
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Sports analysis has recently become popular in research and professional applications. This paper presents a scheme for automatic sports video analysis based on audio clues and specific game context knowledge. We propose a simple, two-step racket-hit detection for achieving accurate event classification for tennis video. To implement the mapping between the sample-level feature space and the semantic-level space, we employ heuristic rules based on specific knowledge of the tennis game. Experimental results have shown that the proposed system can reliably detect the racket hit (at about 90%) and identify meaningful events such as rally, scoring, different types of service, and return. Our system can be operated stand-alone or combined with video analysis and then used for effective and automatic extraction of various tennis events and analysis of tactics with high reliability.