Darts training system based on skeleton estimation

In sports training, coaching by sports instructors is a good way to learn appropriate movements. However, there are fewer instructors for minor sports than for popular sports. The lack of sports instructors is a major problem that causes the decline of sports culture. Darts are a type of minor sport, and there are few instructors. Therefore, most players must study by themselves using books and movies because it is hard to find suitable instructors. In this paper, we propose a dart training system that considers the player's physical mechanics to help players improve their throwing form. We use machine learning algorithms to create the user's skeletal estimation model and select a teacher model based on the user's physique. Thus, the player him/herself can compare the self-throwing motion with that of the instructors. Furthermore, we conduct experiments to evaluate the system's contribution to improving user skills.