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Computer-assisted yoga training system

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Abstract

Self-training is essential in sports exercise. However, without the instruction of a coach, a practitioner may progress to a limited extent. Improper postures may even cause serious harm to muscles and ligaments of the body. Hence, the development of computer-assisted self-training systems for sports exercise is a recently emerging research topic. In this paper, we propose a yoga self-training system, which aims at instructing the practitioner to perform yoga poses correctly, assisting in rectifying poor postures, and preventing injury. Integrating computer vision techniques, the proposed system analyzes the practitioner’s posture from both front and side views by extracting the body contour, skeleton, dominant axes, and feature points. Then, based on the domain knowledge of yoga training, visualized instructions for posture rectification are presented so that the practitioner can easily understand how to adjust his/her posture. Experiments on twelve yoga poses performed by different practitioners validate the feasibility of the proposed system in yoga training.

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Notes

  1. For more details about each yoga pose, please refer to [32].

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Acknowledgments

This research is supported in part by MOST-106-2221-E-009-196, MOST-106-2221-E-035-102, MOST-105-2221-E-009-065, MOST-104-3115-E-009-001, ICTL-103-Q528, and ATU-103-W958.

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Authors and Affiliations

  1. Department of Information Engineering and Computer Science, Feng Chia University, Taichung, 40724, Taiwan

    Hua-Tsung Chen

  2. Department of Computer Science, National Chiao Tung University, Hsinchu, 30010, Taiwan

    Yu-Zhen He & Chun-Chieh Hsu

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  1. Hua-Tsung Chen
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  2. Yu-Zhen He
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  3. Chun-Chieh Hsu
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Correspondence to Hua-Tsung Chen.

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Chen, HT., He, YZ. & Hsu, CC. Computer-assisted yoga training system. Multimed Tools Appl 77, 23969–23991 (2018). https://doi.org/10.1007/s11042-018-5721-2

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  • DOI: https://doi.org/10.1007/s11042-018-5721-2

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