Online 8-Form Tai Chi Chuan Training and Evaluation System Based on Pose Estimation

Exercise at home has already been a common behavior in the current world, especially in the post-COVID-19 era, even some athletes need to do physical fitness at home to keep their state due to the quarantine. So, the importance of online physical training and evaluation is highly increasing. In this work, we build an online 8-form Tai Chi Chuan (TCC) training and evaluation system, which provides a platform for coaches and users to conduct TCC training and evaluation online. Coaches formulate an evaluation rule and upload coaching videos to the platform, then users watch videos online and submit their own recordings, finally, users will get a score of their recordings. To complete this task, we propose a video capture method to record users' sports exercise videos from different perspectives, construct a 3D pose estimation model to identify human pose from captured video, and propose an evaluation model which can judge users' performance and assign a score to each video. To test our proposed models, we make a dataset consisting of key pose frames of TCC, and the key pose frames are extracted from users' TCC exercise videos. We use the dataset to train our models and assign scores to key poses, then compare the results with scores given by professional TCC players. In addition, we add all key pose scores from every single user together and obtain the whole score of an exercise video. The experiment results show that the error between scores assigned by our models and scores given by professional players does not exceed 1.6 in most scoring of a whole exercise video, and Root Mean Square Error (RMSE) is about 0.75 in the scoring of each key pose.