VR 2017

2017 IEEE Virtual Reality (VR), March 18-22, 2017, Los Angeles, CA, USA

Desktop Layout

Poster Session B
Ballroom A/B
Immersive and Collaborative Taichi Motion Learning in Various VR Environments
Tianyu He, Xiaoming Chen, Zhibo Chen, Ye Li, Sen Liu, Junhui Hou, and Ying He
(University of Science and Technology of China, China; City University of Hong Kong, China; Nanyang Technological University, Singapore)
Abstract: Learning “motion” online or from video tutorials is usually inefficient since it is difficult to deliver “motion” information in traditional ways and in the ordinary PC platform. This paper presents ImmerTai, a system that can efficiently teach motion, in particular Chinese Taichi motion, in various immersive environments. ImmerTai captures the Taichi expert’s motion and delivers to students the captured motion in multi-modal forms in immersive CAVE, HMD as well as ordinary PC environments. The students’ motions are captured too for quality assessment and utilized to form a virtual collaborative learning atmosphere. We built up a Taichi motion dataset with 150 fundamental Taichi motions captured from 30 students, on which we evaluated the learning effectiveness and user experience of ImmerTai. The results show that ImmerTai can enhance the learning efficiency by up to 17.4% and the learning quality by up to 32.3%.


Time stamp: 2019-11-15T03:47:51+01:00