Yoga Pose Perfection using Deep Learning
An Algorithm to Estimate the Error in Yogic Poses
DOI:
https://doi.org/10.47611/jsrhs.v10i3.2140Keywords:
yoga, machine learning, posture, yoga pose, yogasana, gesture, computer vision, pose estimation, pose identificationAbstract
AbstractEven with lots of attention and work in the computer vision and artificial intelligence field, human body pose detection is still a daunting task. The application of human pose detection is wide-ranging from health monitoring to public security. This paper focuses on the application in yoga, an art that has been performed for over a millennium. In modern society yoga has become a common method of exercise and there-in arises a demand for instructions on how to do yoga properly. Doing certain yoga postures improperly may lead to injuries and fatigue and hence the presence of a trainer becomes important. As many people don’t have the resources to have a yoga instructor or guide, artificial intelligence can act as a substitute and advise people on their poses. Currently, the research surrounding pose estimation for yoga mainly discusses the classification of yogic poses. In this work, we propose a method, using the Tensorflow MoveNet Thunder model, that allows real-time pose estimation to detect the error in a person's pose, thereby allowing them to correct it.
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Copyright (c) 2021 Satyam Goyal; Animesh Jain
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