Yoga Posture Classification using Computer Vision

  • Madhura Prakash Assistant Professor, Department of Information Science and Engineering, B.N.M Institute of Technology, INDIA
  • Aishwarya S Student, Department of Information Science and Engineering, B.N.M Institute of Technology, INDIA
  • Disha Maru Student, Department of Information Science and Engineering, B.N.M Institute of Technology, INDIA
  • Naman Chandra Student, Department of Information Science and Engineering, B.N.M Institute of Technology, INDIA
  • Varshini V Student, Department of Information Science and Engineering, B.N.M Institute of Technology, INDIA
Keywords: ml5.js, Neural Network, PoseNet

Abstract

There has been over the past few years, a very increased popularity for yoga. A lot of literatures have been published that claim yoga to be beneficial in improving the overall lifestyle and health especially in rehabilitation, mental health and more. Considering the fast-paced lives that individuals live, people usually prefer to exercise or work-out from the comfort of their homes and with that a need for an instructor arises. Hence why, we have developed a self-assisted system which can be used to detect and classify yoga asanas, which is discussed in-depth in this paper. Especially now when the pandemic has taken over the world, it is not feasible to attend physical classes or have an instructor over. Using the technology of Computer Vision, a computer-assisted system such as the one discussed, comes in very handy. The technologies such as ml5.js, PoseNet and Neural Networks are made use for the human pose estimation and classification. The proposed system uses the above-mentioned technologies to take in a real-time video input and analyze the pose of an individual, and classifies the poses into yoga asanas. It also displays the name of the yoga asana that is detected along with the confidence score.

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References

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Published
2021-08-05
How to Cite
Madhura Prakash, Aishwarya S, Disha Maru, Naman Chandra, & Varshini V. (2021). Yoga Posture Classification using Computer Vision. International Journal of Engineering and Management Research, 11(4), 86-89. https://doi.org/10.31033/ijemr.11.4.11