Academic Journal of Computing & Information Science, 2023, 6(6); doi: 10.25236/AJCIS.2023.060608.
Ma Luheng
School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, 230027, China
The analysis of human joint mechanics is of great value in rehabilitation assessment and competitive sports training. There are many limitations in the application of the existing motion capture system, which makes the usage scenarios relatively limited. To solve this problem, this paper proposes a multi-camera 3D motion capture system based on reprojection optimization, and combines the foot mechanics data to obtain the human joint torque. First, build a multi-camera-based motion capture system to obtain human body motion data, reconstruct key points to obtain 3D data, and then propose an accurate key point algorithm based on weight-based reprojection optimization to obtain precise coordinates of key points. Finally, the coordinates of the key points combined with the mechanical data of the foot are calculated by OpenSim to obtain the mechanical data of the human joints. The experimental results show that the capture accuracy of key points is 5% higher than the average accuracy of the traditional least square method, and the analysis of joint mechanics data conforms to the laws of motion, which can be used to guide rehabilitation evaluation and competitive sports.
machine vision; reprojection optimization; human body mechanics analysis
Ma Luheng. Analysis of Human Joint Mechanics Based on High-Precision Unmarked Motion Capture System. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 6: 55-61. https://doi.org/10.25236/AJCIS.2023.060608.
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