Abstract
Activity recognition is useful in many domains. These include biometrics, video -surveillance, human-computer interaction, assisted living, sports arbitration, in-home health monitoring, etc. The health status of an individual can be evaluated and predicted by monitoring and recognizing their activities. Yoga is one such domain that can be used to bring harmony to both body and mind with the help of asana, meditation, and various other breathing techniques. Nowadays in a fast-paced lifestyle, people do not have time to go to yoga classes. Hence, they prefer practicing yoga at home. However, there is a need for a tutor to assess their yoga poses. Hence, the system is presented where the user needs to do the yoga pose which is recognized in real-time video. Then, PoseNet is used to generate key points for the body parts. The identified pose is then compared with the target pose. Based on the comparison status generated by the function, verbal instructions are provided for the user to correct the yoga pose.
Publisher
International Journal for Research in Applied Science and Engineering Technology (IJRASET)
Cited by
2 articles.
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1. Yoga Pose Classification Using CNN with PReLU Activation;2024 International Conference on Advancements in Power, Communication and Intelligent Systems (APCI);2024-06-21
2. A Novel Approach for Developing Inclusive Real-Time Yoga Pose Detection for Health and Wellness Using Raspberry pi;2023 7th International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS);2023-11-02