Abstract
In sports training, the traditional image analysis method has the problems of low precision and easy to be disturbed by the environment. The aim of this research is to simulate the motion training image analysis by using optical fiber sensor based on human posture tracking algorithm. By this method, the precision of image analysis can be improved and the dependence on environment can be reduced. The key bone points of exerciser are tracked and located by using the human posture tracking algorithm. Then, the motion information related to bone points is collected by optical fiber sensor, and the motion information is converted into images by optical technology and analyzed. The effectiveness of the optical fiber sensor based on human posture tracking algorithm in the analysis of motion training images is verified through the simulation experiments of several motion training scenarios. Compared with the traditional method, the proposed method has higher accuracy and stability, which can improve the effect of image analysis, and has potential application value in practical training.
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The paper was supported by Foundation Item: Humanities and Social Science Research Planning Project of Chongqing Education Commission in 2022 (No: 22SKGH101).
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SW has done the first version, XL has done the simulations. All authors have contributed to the paper’s analysis, discussion, writing, and revision.
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Wei, S., Li, X. Simulation of optical fiber sensor in motion training image analysis system based on human posture tracking algorithm. Opt Quant Electron 56, 299 (2024). https://doi.org/10.1007/s11082-023-05996-y
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DOI: https://doi.org/10.1007/s11082-023-05996-y