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YOGA POSE ESTIMATION
ISSN: 2582 - 9130
Publisher: author
YOGA POSE ESTIMATION
Indexed in
Technology and Engineering
ARTICLE-FACTOR
1.3
Article Basics Score: 3
Article Transparency Score: 3
Article Operation Score: 3
Article Articles Score: 2
Article Accessibility Score: 3
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International Category Code (ICC):
ICC-1802
Publisher: Krishma Publication
International Journal Address (IAA):
IAA.ZONE/2582384239130
eISSN
:
2582 - 9130
VALID
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Abstract
Human pose estimation is a deep-rooted problem in computer vision that has exposed many challenges in the past. Analyzing human activities is beneficial in many fields like video- surveillance, biometrics, assisted living, at-home health monitoring etc. With our fast-paced lives these days, people usually prefer exercising at home but feel the need of an instructor to evaluate their exercise form. As these resources are not always available, human pose recognition can be used to build a self-instruction exercise system that allows people to learn and practice exercises correctly by themselves. This project lays the foundation for building such a system by discussing various machine learning and deep learning approaches to accurately classify yoga poses on prerecorded videos and also in real-time. The project also discusses various pose estimation and key point detection methods in detail and explains different deep learning models use...
