Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 6, Issue 2


Published
on

November 22, 2021


Pages

203-216


DOI

Article

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

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Authors

Qiuju Chen Affiliation:
Hainan College of Economics and Business, Haikou Hainan, 571127, China
and Rayan Atteah Alsemmeari Affiliation:
Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia


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.


Keywords

motion capture, free editing, skeleton model, feature plane, similarity matching, pose analysis, scientific training, 34A34


Citation

Chen, Q. & Alsemmeari, R. A. (2021). Research on aerobics training posture motion capture based on mathematical similarity matching statistical analysis. Applied Mathematics and Nonlinear Sciences, 6(2), 203–216. https://doi.org/10.2478/amns.2021.2.00055

Published by: Engineering Journals

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