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Ball Hit Detection in Table Tennis Games Based on Audio Analysis

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3 Author(s)
Bin Zhang ; Dept. of Electron. Eng., Tsinghua Univ., Beijing ; Weibei Dou ; Liming Chen

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

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Pattern Recognition, 2006. ICPR 2006. 18th International Conference on  (Volume:3 )

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