Abstract:
The centuries-old Indian discipline of yoga is known worldwide for its spiritual, physical, and mental benefits. It involves difficult poses. Any wrong position during a yoga session might be ineffective and uncomfortable, just like any other workout. This requires a trainer to oversee the meeting and correct the individual’s position. Since not all clients have access to a trainer, a computerized reasoning-based program could recognize yoga poses and provide individualized feedback to enhance structure.
We created our Yoga Pose Detection System to recognize yoga stances and provide individualized feedback to help users improve. Our algorithm detects Chair, Cobra, Dog, Shoulder Stand, Triangle, Tree, Warrior, and No Pose yoga positions.
The Yoga Pose Detection System has one module: User. They can upload a photo of a yoga stance or pose in front of a camera, and the system will identify and display the pose.
The method recognizes Chair, Cobra, Dog, Shoulder Stand, Triangle, Tree, Warrior, and No Pose yoga poses. This project uses OpenCV, dlib, OpenPose, and MediaPipe. OpenPose is the first real-time multi-person system to recognize body, foot, hand, and facial key points on single photos. This project uses Django. The Front End uses HTML, CSS, and JavaScript. The back end uses MySQL.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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