Miss Yoga: A Yoga Assistant Mobile Application Based on Keypoint Detection

This paper demonstrates a Yoga assistant mobile application based on human-keypoints detection models, which imitates the scene that real Yoga tutors guide and supervise their students to do Yoga via the video chat. In order to provide humanize, safe and convenient service, the core function is designed as hands-free using voice service, and embedding fast and accurate models to detect keypoints and calculate the scores. In addition, we propose an improved algorithm to calculate scores that can be applied to all poses. Our application is evaluated on different Yoga poses under different scenes, and its robustness is guaranteed.