“Visualizing Expert Motion for Guidance in a VR Ski Simulator” by Nozawa, Wu, Perteneder and Koike
Conference:
Type(s):
Entry Number: 64
Title:
- Visualizing Expert Motion for Guidance in a VR Ski Simulator
Presenter(s)/Author(s):
Abstract:
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.
References:
- Vladimir Aleshin, Valery Afanasiev, Alexander Bobkov, Stanislav Klimenko, Vitaly Kuliev, and Dmitry Novgorodtsev. 2011. Visual 3d perception of the ski course and visibility factors at virtual space. In Cyberworlds (CW), 2011 International Conference on. IEEE, 222–226.
- Vladimir Aleshin, Stanislav Klimenko, Mikhail Manuilov, and Leonid Melnikov. 2009. Alpine skiing and snowboarding training system using in-duced virtual environment. Science and Skiing IV (2009).
- Jacky CP Chan, Howard Leung, Jeff KT Tang, and Taku Komura. 2011. A virtual reality dance training system using motion capture technology. IEEE Transactions on Learning Technologies 4, 2 (2011), 187–195.
- Shoichi Hasegawa, Seiichiro Ishijima, Fumihiro Kato, Hironori Mitake, and Makoto Sato. 2012. Realtime sonification of the center of gravity for skiing. In Proceedings of the 3rd Augmented Human International Conference. ACM, 11.
- Atsuki Ikeda, Dong Hyun Hwang, and Hideki Koike. 2018. AR based Self-sports Learning System using Decayed Dynamic TimeWarping Algorithm. In ICAT-EGVE 2018 – International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments, Gerd Bruder, Shunsuke Yoshimoto, and Sue Cobb (Eds.). The Eurographics Association. https://doi.org/10.2312/egve.20181330
- Ahmad Hassan Kobeissi, Hussein Chible, Riccardo Berta, Alessandro De Gloria, and Francesco Bellotti. 2017. Design and implementation of an IoT system for enhancing proprioception training. In Microelectronics (ICM), 2017 29th International Conference on. IEEE, 1–4.
Keyword(s):
Additional Images:
![©Takayuki Nozawa, Erwin Wu, Florian Perteneder, and Hideki Koike](https://history.siggraph.org/wp-content/uploads/2021/10/2019-Poster-64-Nozawa_Visualizing-Expert-Motion-03.jpg)
![©Takayuki Nozawa, Erwin Wu, Florian Perteneder, and Hideki Koike](https://history.siggraph.org/wp-content/uploads/2021/10/2019-Poster-64-Nozawa_Visualizing-Expert-Motion-04.jpg)
Acknowledgements:
This work was supported by JST CREST under Grant No.: JPMJCR17A3.