Sports skill discrimination with motion frequency analysis
Sports skill discrimination with motion frequency analysis
复制标题
通过运动频率分析进行运动技能判别
DOI：
10.1109/ftc.2016.7821618
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Masumi Yajima
中科院分区：
文献类型：
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作者：
T. Maeda;Masumi Yajima
以排球进攻技术为研究对象，运用运动图像数据对运动技术进行判别。我们试图证明这一假设，专家技能，而不是新手技能具有相对较低的频率动作，人类的姿势控制的相似性。为此，我们进行实验，并分析运动技能的运动频率使用时间序列的排球攻击运动图片。本文利用高速摄像编码器记录的运动图像数据对排球比赛进行分析，在不使用人体骨骼模型等物理信息的情况下，从运动图像数据中提取四个标记点的时间序列数据，并利用快速傅立叶变换（FFT）和聚类数据挖掘方法进行分析。实验结果发现，新手数据的y轴上有更多的高频数据，这意味着新手运动有高频运动，这可能支持我们的假设。
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.