Authors:
Shimpei Aihara
1
;
Takara Sakai
2
and
Akira Shionoya
2
Affiliations:
1
Department of Sport Science and Research, Japan Institute of Sport Sciences, Tokyo, Japan
;
2
Department of Management and Information Systems Science, Nagaoka University of Technology, Niigata, Japan
Keyword(s):
Wheelchair Sports, Positioning System, Monocular Camera, Deep Learning.
Abstract:
Recently, tracking systems to measure player positions have been introduced in the sports domain. However, wheelchair sports have not been considered extensively. In addition, user-friendly and low-cost systems for wheelchair sports are uncommon. Thus, in this paper, we propose a method to calculate the kinematic data of wheelchair athletes on a playing field (i.e., player positions and wheelchair directions) using images acquired by a monocular camera. The proposed method was evaluated experimentally, and the root mean square error of the position accuracy was 0.11 m, and the mean average error of the direction accuracy was 6.78 degrees. The results demonstrate that the proposed method outperforms existing tracking methods in terms of accuracy. The findings of this study suggest that it is possible to acquire kinematic data of wheelchair athletes using a simple method, which we expect to contribute to improvement analysis of the wheelchair athlete performance.