Research on aerobics training posture motion capture based on mathematical similarity matching statistical analysis

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Abstract

Aiming at the freely editable characteristics of human motion posture, a human skeleton model is extracted, and a human motion posture model library is established. The application of motion capture system in dance training is analysed, and a method based on similarity matching between feature planes is proposed to calculate each model. Parameters of motion data between parts are obtained. After verification, the method has high accuracy and robustness for the analysis of human poses so that dancers can accurately compare the differences with standard dance movements and provide theoretical support for dancers to perform scientific dance training.

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Chen, Q., & Alsemmeari, R. A. (2022). Research on aerobics training posture motion capture based on mathematical similarity matching statistical analysis. Applied Mathematics and Nonlinear Sciences, 7(2), 203–216. https://doi.org/10.2478/amns.2021.2.00055

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