Sports Skill Analysis using Motion Frequency

MASUMI, YAJIMA and TAKESHI, MATSUDA and TOSHIYUKI, MAEDA (2016) Sports Skill Analysis using Motion Frequency. In: Fifth International Conference on Advances in Computing, Control and Networking - ACCN 2016, 25-26 September 2016, Bangkok, Thailand.

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This paper addresses sports skill discrimination using motion picture data, focused on volleyball attack skill. We attempt to certify the hypothesis that expert skills have relatively low frequency motions rather than novice skills as the similarity of human postural control. For this purpose we proceed experiments and analyze sports skills as for frequency of motion using time series motion pictures of volleyball attacks. In this paper, volleyball play is analyzed with motion picture data recorded by hi-speed cam-coder, where we do not use physical information such as body skeleton model, and so on. Time series data are obtained from the motion picture data with four marking points, and analyzed using Fast Fourier Transform (FFT) and clustering data mining method. As the experiment results, we have found that y-axes of novice data may have more highfrequency data, and that implies novice motions may have high frequency motions, and that may support our hypothesis.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Time Series Data, Sports Skill Analysis, Motion Picture, Fast Fourier Transform
Depositing User: Mr. John Steve
Date Deposited: 22 Mar 2019 06:57
Last Modified: 22 Mar 2019 06:57

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