While humans are quite good at copying motions from others, it is difficult to do so in a dynamic sport such as skiing. Hence, we propose a virtual reality ski training system, which visualizes prerecorded expert motion in different ways and enables users to learn by copying. The system is based on a commercial indoor ski simulator, a VR headset, and two VR trackers to capture the ski's motion. Users can control their skis on the virtual ski slope and improve their skills by following a digital avatar of the expert skier replayed in front of them. We investigate 3 types of visualizations for training: Graphs to visualize the angle of feet compared to the expert, periodic copies of the expert's pose to show the spatial and temporal motion of the key movements, and a more minimal ribbon-trace of the leading skier to point out the optimized trajectory.
[1]
Makoto Sato,et al.
Realtime sonification of the center of gravity for skiing
,
2012,
AH '12.
[2]
Taku Komura,et al.
A Virtual Reality Dance Training System Using Motion Capture Technology
,
2011,
IEEE Transactions on Learning Technologies.
[3]
Atsuki Ikeda,et al.
AR based Self-sports Learning System using Decayed Dynamic TimeWarping Algorithm
,
2018,
ICAT-EGVE.
[4]
Hussein Chible,et al.
Design and implementation of an IoT system for enhancing proprioception training
,
2017,
2017 29th International Conference on Microelectronics (ICM).
[5]
Alexander Bobkov,et al.
Visual 3D Perception of the Ski Course and Visibility Factors at Virtual Space
,
2011,
2011 International Conference on Cyberworlds.