Yoga Asana Identification: A Deep Learning Approach

Author:

Jose Josvin,Shailesh S

Abstract

Abstract Yoga is a healthy practice that originated from India, to rejuvenate a man in his physical, mental, and spiritual wellness. Moving with the brisk technology advancements, there is a vast opportunity for computational probing in all social domains. But still, the utilization of artificial intelligence and machine learning techniques for applying to an interdisciplinary domain like yoga is quite challenging. In this work, a system that recognizes a yoga posture from an image or a frame of a video has been developed with the help of deep learning techniques like convolutional neural networks (CNN) and transfer learning. We have considered images of 10 different asanas for training the model as well as evaluating the prediction accuracy. The prediction model backed with transfer learning shows promising results with 85% prediction accuracy and this system can be considered as an initial step to build an automated yoga image and video analysis tool.

Publisher

IOP Publishing

Subject

General Medicine

Cited by 36 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. CAM based fine-grained spatial feature supervision for hierarchical yoga pose classification using multi-stage transfer learning;Expert Systems with Applications;2024-09

2. Transfer Learning Based Yogic Posture Recognition System Using Deep Pre-trained Features;SN Computer Science;2024-08-01

3. HARNet: design and evaluation of a deep genetic algorithm for recognizing yoga postures;Signal, Image and Video Processing;2024-05-15

4. Technological Insights into Yoga Posture Recognition: A State-of-the-Art Review;2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE);2024-05-09

5. DensePoseCompare: A Comparative Study of DenseNet Models in Yoga Pose Classification;2024 International Conference on Cognitive Robotics and Intelligent Systems (ICC - ROBINS);2024-04-17

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