Students from MVJ College of Engineering’s Computer Science and Engineering Department have developed a yoga pose tracking method so that beginners do not perform any poses incorrectly. The system evaluates a yoga position of a learner by identifying the pose calculating the difference in body angles between a teacher’s stance and that of a user, thus displaying the errors between learner and instructor.
Its purpose is to estimate multi-person human poses in videos and assign unique instance IDs for each key point across the frame. The team of students who were involved in the project included Deepti Singh, Deepak Pandey, Hima V S and Bhaskar Katragadda.
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“Nowadays, a lot of people practice yoga at home by watching TV/videos. However, without the instruction of a coach, a practitioner may perform poses incorrectly and it may not be easy for beginners to identify this by themselves. In this context, students from the Computer Science and Engineering Department of MVJ College of Engineering have developed a Yoga Pose Tracking method,” the university said.
The students have used media pipe blaze pose, which is an on-device body pose tracking approach. It delivers real-time performance on mobile phones and delivers super-real-time performance by leveraging GPU inference. It entails a two-step detector-tracker ML pipeline for estimating the exact pose. This pipeline initially locates the pose region-of-interest (ROI) inside the picture using a detector after which the tracker forecasts all 33 posture important points from this ROI.
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The Computer Science and Engineering students who worked on the project said, “It was a great opportunity to work together and develop the devise as our ambitious ideas turned real and tangible, and were within reach. It’s a new approach to assisting individuals in improving their lives and contributing to the development of a healthy community as a whole. In the future, we aspire to work on socially useful projects like this.”
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