An Adaptive Tai-Chi-Chuan AR Guiding System Based on Speed Estimation of Movement
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Augmented Reality (AR) headsets has become a potential device as an auxiliary tool for practicing physical activities such like Tai-Chi Chuan (TCC). Although some learning systems can display the virtual coach movement in AR headsets, the playing speed cannot be adjusted appropriately just like a real coach stand next to you. In most of the learning system, the common approach is using controller to control the playback system under a specific speed. Once user want to speed up or speed down, he has to do these commands via a controller. In this work, we propose a TCC learning system which will real time detect the delay time between current action of user and virtual coach. After obtaining the delay time, our learning system will adjust speed of virtual coach automatically. With real time speed adjustment, learners can practice TCC with their own pace and virtual coach will slow down or speed up to follow learners’ movement.
KeywordsReal-time speed estimation Physical activity learning Mixed reality Tai-Chi Chuan
This study is partially supported by Ministry of Science and Technology, Taiwan (R.O.C.), under grant MOST 107-2221-E-369 -001 -MY2 and supported by the “III Innovative and Prospective Technologies Project” of the Institute for Information Industry which is subsidized by the Ministry of Economy Affairs of the Republic of China.
- 1.Velloso, E., Bulling, A., Gellersen, H.: MotionMA: motion modelling and analysis by demonstration. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1309–1318. ACM, April 2013Google Scholar
- 2.Anderson, F., Grossman, T., Matejka, J., Fitzmaurice, G.: YouMove: enhancing movement training with an augmented reality mirror. In: Proceedings of the 26th Annual ACM Symposium on User Interface Software and Technology, pp. 311–320. ACM, October 2013Google Scholar
- 3.Tominaga, J., Kawauchi, K., Rekimoto, J.: Around me: a system with an escort robot providing a sports player’s self-images. In: Proceedings of the 5th Augmented Human International Conference, p. 43. ACM, March 2014Google Scholar
- 4.Han, P.H., Chen, Y.S., Zhong, Y., Wang, H.L., Hung, Y.P.: My Tai-Chi coaches: an augmented-learning tool for practicing Tai-Chi Chuan. In: Proceedings of the 8th Augmented Human International Conference, p. 25. ACM, March 2017Google Scholar
- 5.Ukai, Y., Rekimoto, J.: Swimoid: a swim support system using an underwater buddy robot. In: Proceedings of the 4th Augmented Human International Conference, pp. 170–177. ACM, March 2013Google Scholar
- 6.Drobny, D., Borchers, J.: Learning basic dance choreographies with different augmented feedback modalities. In: CHI 2010 Extended Abstracts on Human Factors in Computing Systems, pp. 3793–3798. ACM, April 2010Google Scholar
- 8.Graether, E., Mueller, F.: Joggobot: a flying robot as jogging companion. In: CHI 2012 Extended Abstracts on Human Factors in Computing Systems, pp. 1063–1066. ACM, May 2012Google Scholar
- 9.Higuchi, K., Shimada, T., Rekimoto, J.: Flying sports assistant: external visual imagery representation for sports training. In: Proceedings of the 2nd Augmented Human International Conference, p. 7. ACM, March 2011Google Scholar