Abstract: Sports skill discrimination using motion picture data, focused on volleyball attack skill is performed. 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. We carry out experiments and analyze sports skills as for frequency of motion using time series motion pictures of volleyball attacks. The 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. From motion picture data Time series data are obtained 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 have more high-frequency data, and that implies novice motions have high frequency motions, and that may support our hypothesis.

Keywords: Motion picture data, high speed camcorder, Fast Fourier Transform (FFT), Clustering

| DOI: 10.17148/IJIREEICE.2019.7216