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Recognition Method of Wushu Human Complex Movement Based on Bone Point Feature.

Anping Li1, Ruijie Zhang2,3, Lingrong Tao4

  • 1Department of Physical Education and Research, Yang-En University, Quanzhou 362014, China.

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This study introduces a novel Wushu (Chinese martial arts) movement recognition method using bone point features. The technique improves accuracy and speed for complex human motion identification.

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Area of Science:

  • Biomechanics
  • Computer Vision
  • Sports Science

Background:

  • Current Wushu movement recognition methods suffer from low accuracy due to imperfect kinetic energy models.
  • Accurate recognition of complex human movements is crucial for performance analysis and training in Wushu.

Purpose of the Study:

  • To design an improved method for recognizing complex human movements in Wushu.
  • To enhance recognition accuracy and efficiency by utilizing bone point features and an optimized kinetic energy model.

Main Methods:

  • A novel method for complex human motion recognition based on bone point features was developed.
  • The method incorporates the trajectory of the human center of gravity and establishes a joint kinetic energy model.
  • A threshold for local spatial differences of human bones was set using the hip joint as the central node to optimize the identification process.

Main Results:

  • The proposed method achieved correct recognition rates of 90.1% and 92.7% for different Wushu actions.
  • Action identification times were recorded at 1.2s and 1.41s, demonstrating rapid processing.
  • The results indicate effective and quick identification of complex movements by leveraging bone point feature information.

Conclusions:

  • The bone point feature-based method significantly improves the accuracy and efficiency of Wushu complex human motion recognition.
  • This approach offers a viable solution to the limitations of existing kinetic energy models in motion recognition.