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  Published Paper Details:

  Paper Title

YOGA ASSISTANT: A YOGA POSTURE DETECTION & CORRECTION SYSTEM

  Authors

  Shubham Santosh Rokade,  Suyash Machhindra Kamble,  Parth Santosh Kshirsagar,  Anish Janardhan Kakar,  Prof.K.S.Hangargi

  Keywords

Self-learning, Machine Learning, Yoga Pose Detection

  Abstract


In order to study and evaluate yoga postures, this final-year project covers the design, development, and implementation of a Yoga Pose Detection System that combines computer vision and machine learning approaches. By giving practitioners immediate feedback and direction, the method seeks to improve the quality of the yoga practice and help practitioners achieve better alignment, form, and general well-being. The research uses cutting-edge image processing algorithms to identify and extract important body landmarks and information from pictures or videos of people doing yoga positions. Utilizing a trained machine learning model, the system accurately identifies and classifies various positions, offering real-time feedback on alignment, balance, and good posture. Experts seeking guidance from beginners to seasoned practitioners refining their skills can all benefit from the offered solution.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2402005

  Paper ID - 250641

  Page Number(s) - a43-a48

  Pubished in - Volume 12 | Issue 2 | February 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Shubham Santosh Rokade,  Suyash Machhindra Kamble,  Parth Santosh Kshirsagar,  Anish Janardhan Kakar,  Prof.K.S.Hangargi,   "YOGA ASSISTANT: A YOGA POSTURE DETECTION & CORRECTION SYSTEM", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 2, pp.a43-a48, February 2024, Available at :http://www.ijcrt.org/papers/IJCRT2402005.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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