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Motion feature quantization of athletic sports training based on fuzzy neural network theory

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Abstract

Human frame structure model of sports movement and mathematical indication method of sports action were proposed in the thesis and the method of feature quantization and mode analysis for sports action was discussed. The method could be easily understood and realized based on graphic pattern discrimination and multimedia database technology. Meanwhile, fuzzy neural network theory was introduced to conduct action feature quantization so as to realize full automatic recognition of action feature quantization of athletic sports training. Finally, the effectiveness of action feature quantization method of athletic sports training based on fuzzy neural network theory was verified through quantitative example analysis of style feature variables of a complete set of Nanquan action.

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Acknowledgement

A Study on Sports Cultural Crisis of Land-losing Peasants under the Opportunity of New Urbanization in Hunan Province.

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Authors and Affiliations

  1. College of Physical Education, Hunan University, Changsha, 410028, Hunan, China

    Xinke Leng

  2. College of Physical Education, Hunan First Normal University, Changsha, 410205, Hunan, China

    Huijun Jiang, Xunhao Zou & Xiaoling Zeng

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  1. Xinke Leng
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  2. Huijun Jiang
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  3. Xunhao Zou
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  4. Xiaoling Zeng
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Correspondence to Xinke Leng.

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Leng, X., Jiang, H., Zou, X. et al. Motion feature quantization of athletic sports training based on fuzzy neural network theory. Cluster Comput 22 (Suppl 2), 4631–4638 (2019). https://doi.org/10.1007/s10586-018-2231-y

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  • DOI: https://doi.org/10.1007/s10586-018-2231-y

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