Self-Training System for Tennis Shots with Motion Feature Assessment and Visualization

This paper describes a prototype self-training system for tennis forehand shots that allows trainees to practice their motion forms by themselves. Our system uses a motion capture device to record a trainee's motion, and visualizes the differences between the features of the trainee's motion and the correct motion as performed by an expert. This system enables trainees to understand the errors in their motion and how to reduce or eliminate them. In this study, we classified the motion features and corresponding visualization methods using one-dimensional spatial, rotational, and temporal features based on the key sporting poses. We also developed a statistical model for the motion features, allowing the system to assess and prioritize all features of a trainee's motion. This research focuses on the motion of a tennis forehand shot and evaluates our prototype through several user experiments.