Recognition method of throwing force of athlete based on multi-class SVM

  • Authors:

  • Jinghua Ma;Yunjian Ge;Jianhe Lei;Quanjun Song;Yu Ge;Yong Yu

  • Affiliations:

  • Robot Sensor Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, P.R. China;Robot Sensor Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, P.R. China;Robot Sensor Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, P.R. China;Robot Sensor Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, P.R. China;Robot Sensor Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, P.R. China;Robot Sensor Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, P.R. China

  • Venue:
  • ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
  • Year:
  • 2006

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Abstract

A novel recognition method of throwing force of athlete combined with wavelet and multi-class support vector machine is introduced in the paper, which is based on the analysis of motion characters of gliding shot put. Utilizing the digital shot based on a three dimensional accelerometer, we get the three dimensional throwing forces in real time. Through wavelet transform, the general characteristics of force information are picked up. Then the general characteristics are input into the classifier for recognition of throwing force curves. The analysis provides the scientific basis for the motion training and instruction of shot put. The experiment shows that the method not only has high anti-noise ability and improves the recognition efficiency, but also decreases the burden of system and improves the recognition speed.