|[Oshita Lab.][Research Theme]||[Japanese]|
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.
- Tomohiko Mukai, Tokyo Metropolitan University
- Shigeru Kuriyama, Toyohashi University of Technology
- Masaki Oshita, Takumi Inao, Shunsuke Ineno, Tomohiko Mukai, Shigeru Kuriyama, "Development and Evaluation of a Self-Training System for Tennis Shots with Motion Feature Assessment and Visualization", The Visual Computer, 13 pages, Springer, May 2019. [Journal]
- Masaki Oshita, Takumi Inao, Tomohiko Mukai, Shigeru Kuriyama, "Self-Training System for Tennis Shots with Motion Feature Assessment and Visualization", International Conference on Cyberworlds 2018, pp. 82-89, Singapore, October 2018. [PDF] [Video]
- Takumi Inao, Masaki Oshita, Tomohiko Mukai, Shigeru Kuriyama, "Visualization of Motion Features for Sports Training System Using Kinect", 14th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry (VRCAI 2015), Posters and Demos, 2 pages, Kobe, Japan, November 2015.
AcknowledgmentsThis work was supported in part by a Grant-in-Aid for Scientific Research (No. 15H02704) from the Japan Society for the Promotion of Science (JSPS).