Issue |
MATEC Web Conf.
Volume 135, 2017
8th International Conference on Mechanical and Manufacturing Engineering 2017 (ICME’17)
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Article Number | 00059 | |
Number of page(s) | 14 | |
DOI | https://doi.org/10.1051/matecconf/201713500059 | |
Published online | 20 November 2017 |
Performance of Dual Depth Camera Motion Capture System for Athletes’ Biomechanics Analysis
Faculty of Mechanical and Manufacturing Engineering Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia
* Corresponding author: zamani@uthm.edu.my
Motion capture system has recently being brought to light and drawn much attention in many fields of research, especially in biomechanics. Marker-based motion capture systems have been used as the main tool in capturing motion for years. Marker-based motion capture systems are very pricey, lab-based and beyond reach of many researchers, hence it cannot be applied to ubiquitous applications. The game however has changed with the introduction of depth camera technology, a markerless yet affordable motion capture system. By means of this system, motion capture has been promoted as more portable application and does not require substantial time in setting up the system. Limitation in terms of nodal coverage of single depth camera has widely accepted but the performance of dual depth camera system is still doubtful since it is expected to improve the coverage issue but at the same time has bigger issues on data merging and accuracy. This work appraises the accuracy performance of dual depth camera motion capture system specifically for athletes’ running biomechanics analysis. Kinect sensors were selected to capture motions of an athlete simultaneously in three-dimension, and fused the recorded data into an analysable data. Running was chosen as the biomechanics motion and interpreted in the form of angle-time, angleangle and continuous relative phase plot. The linear and angular kinematics were analysed and represented graphically. Quantitative interpretations of the result allowed the deep insight of the movement and joint coordination of the athlete. The result showed that the root-mean-square error of the Kinect sensor measurement to exact measurement data and rigid transformation were 0.0045 and 0.0077291 respectively. The velocity and acceleration of the subject were determined to be 3.3479 ms-1 and –4.1444 ms-2. The result showed that the dual Kinect camera motion capture system was feasible to perform athletes' biomechanics analysis.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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