AR based Self-sports Learning System using Decayed Dynamic Time Warping Algorithm
Published in International Conference on Artificial Reality and Telexistence, Eurographics Symposium on Virtual Environments 2018 (ICAT-EGVE 2018, Short paper), 2018
Recommended citation: Ikeda et al. "AR based Self-sports Learning System using Decayed Dynamic Time Warping Algorithm." ICAT-EGVE 2018. 2018. https://diglib.eg.org/handle/10.2312/egve20181330
Authors
Ikeda Atsuki, Dong-Hyun Hwang, and Hideki Koike
Tokyo Institute of Technology
Abstract
A self-sports learning system that provides users with real-time multimodal feedback about differences between a user’s motion and an expert’s motion is proposed. We also propose the Decayed Dynamic Time Warping algorithm, which allows the user to change the motion speed dynamically and repeat a target motion without additional operations. The user can thus imitate an expert’s motion conveniently and accurately. The proposed system involves training and replay modes. In the training mode, the system provides audio-visual feedback to help the user imitate the expert’s motion. The replay mode allows the user to compare their motion to that of the expert. An augmented reality head-mounted display delivers feedback and provides an immersive three-dimensional training experience.
Photo
[
]