Sports skill discrimination with motion frequency analysis

Maeda, T; Yajima, M

doi:10.1109/FTC.2016.7821618

Sports skill discrimination with motion frequency analysis

Lookup NU author(s): Professor Toshiyuki Maeda, Professor Masumi Yajima

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.

Abstract

© 2016 IEEE.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 have more high-frequency data, and that implies novice motions have high frequency motions, and that may support our hypothesis.