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Estimation of Yoga Postures Using Machine Learning Techniques.

D Mohan Kishore¹, S Bindu², Nandi Krishnamurthy Manjunath¹

¹Division of Yoga and Life Sciences, Swami Vivekananda Yoga Anusandhana Samsthana (S-VYASA), Bengaluru, Karnataka, India.

International Journal of Yoga

|November 4, 2022

Summary

This summary is machine-generated.

This study introduces deep learning models to help yoga practitioners maintain correct poses. MediaPipe demonstrated the highest accuracy in estimating yoga postures, aiding safe practice.

Keywords:

Artificial intelligence deep learning machine learning techniques pose estimation techniques skeleton and yoga

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Area of Science:

* Computer Vision
* Artificial Intelligence
* Health & Wellness

Background:

* Yoga practice surged during the pandemic, with many new practitioners lacking guidance.
* Ensuring correct yoga postures (asanas) is crucial for safety and efficacy.
* Traditional methods for pose correction can be resource-intensive.

Purpose of the Study:

* To develop and evaluate deep learning models for automated yoga pose estimation.
* To assist yoga practitioners, especially beginners, in achieving correct asanas.
* To compare the performance of different deep learning architectures for this task.

Main Methods:

* Four deep learning architectures (EpipolarPose, OpenPose, PoseNet, MediaPipe) were implemented.
* Models were trained using an authentic yoga posture image database from S-VYASA University.
* The database included five common yoga poses: tree, triangle, half-moon, mountain, and warrior poses.

Main Results:

* All implemented deep learning architectures were capable of estimating yoga poses.
* A comparative analysis of estimation accuracy was performed for each architecture.
* The MediaPipe architecture exhibited superior accuracy in yoga pose estimation.

Conclusions:

* Deep learning models can effectively estimate yoga poses from images.
* MediaPipe is the most accurate architecture for real-time yoga pose correction applications.
* This technology can support safe and effective yoga practice for a wider audience.