Yoga Pose Detection
Shrinivas Nagargoje, Adesh Shinde, Pranav Tapadiya, Om C. Shinde, Prof. Anita Devkar · International Journal for Research in Applied Science and Engineering Technology · 2023
Abstract: This paper describes a real-time yoga pose detection system that can accurately classify and detect yoga poses in images using Convolutional Neural Networks (CNNs) and OpenPose. By using OpenPose, the system generates a 3D joint map of the person's body, which is then used as input for linear regression to detect the individual yoga pose. The system is suitable for real-time applications, and is expected to be used in fitness centers, yoga studios, and even for personal use. Additionally, the system can also be used to track the progress of yoga practitioners, allowing them to analyze their performance and improve their practice. Furthermore, the proposed system is expected to benefit the yoga industry by providing a low- cost, efficient, and accurate means to detect poses.