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Ball Hit Detection in Table Tennis Games Based on Audio Analysis
Hong Kong August 20-August 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.31418th International Conference on Patt ...
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Bin Zhang, Tsinghua University, Beijing, China
Weibei Dou, Tsinghua University, Beijing, China
Liming Chen, LIRIS CNRS UMR 5205 Ecole Centrale de Lyon , France
As bearer of high level semantics, audio signal is being more and more used in content-based multimedia retrieval. In this paper, we investigate the ball hit detection for sports games and propose a novel approach to detect ball hits. By employing Energy Peak Detection (EPD) and Mel Frequency Cepstral Coefficient-based (MFCC-based) Refinement (MBR), high precision (91%) and adequate recall (73%) of ball hit detection are achieved with a low computational complexity and an easy training process. The proposed algorithm can be applied in audio content-based highlight detection systems and provide valuable information for semantical understanding of sports games.
Citation:
Bin Zhang, Weibei Dou, Liming Chen, "Ball Hit Detection in Table Tennis Games Based on Audio Analysis," icpr, vol. 3, pp.220-223, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006
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