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

Qiuju Chen,Rayan Atteah Alsemmeari

doi:10.2478/amns.2021.2.00055

Qiuju Chen, Rayan Atteah Alsemmeari

Open Access

https://doi.org/10.2478/amns.2021.2.00055

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Abstract

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.

Highlights

With the rapid development of human motion simulation and virtual reality, motion capture technology has been widely used in the fields of film and television production, medical rehabilitation, animation games and other fields, achieving the perfect combination of three-dimensional virtual world and reality technology
An optical motion capture system is used to track and detect the dancer’s dance movements in segments, and a real-time analysis method of moving human poses based on similarity matching between feature planes is proposed
Determine 7 feature planes based on feature points, extract 13 feature vectors and calculate human poses based on the motion characteristics of key parts of the dance action feature correlation coefficient

Summary

Introduction

With the rapid development of human motion simulation and virtual reality, motion capture technology has been widely used in the fields of film and television production, medical rehabilitation, animation games and other fields, achieving the perfect combination of three-dimensional virtual world and reality technology. An optical motion capture system is used to track and detect the dancer’s dance movements in segments, and a real-time analysis method of moving human poses based on similarity matching between feature planes is proposed. It improves the efficiency of posture analysis and improves the teaching quality in real-time analysis, which has played an important role in the digital teaching of dance movements and scientific development.

Near-infrared high-sensitivity digital camera captures human motion

Get skeleton data in real time

Similarity matching of traditional 3D models

Calculation of differences between feature poses

Analysis of experimental results

Conclusion