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2017 IEEE Virtual Reality (VR) (2017)
Los Angeles, CA, USA
March 18, 2017 to March 22, 2017
ISSN: 2375-5334
ISBN: 978-1-5090-6648-3
pp: 307-308
Tianyu He , School of Information Science and Technology, University of Science of Technology of China, China
Xiaoming Chen , School of Information Science and Technology, University of Science of Technology of China, China
Zhibo Chen , School of Information Science and Technology, University of Science of Technology of China, China
Ye Li , Department of Computer Science, City University of Hong Kong, SAR China
Sen Liu , Department of Computer Science, City University of Hong Kong, SAR China
Junhui Hou , Department of Computer Science, City University of Hong Kong, SAR China
Ying He , School of Computer Engineering, 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%.
INDEX TERMS
Resists, Avatars, Training, Virtual environments, Layout
CITATION

T. He et al., "Immersive and collaborative Taichi motion learning in various VR environments," 2017 IEEE Virtual Reality (VR), Los Angeles, CA, USA, 2017, pp. 307-308.
doi:10.1109/VR.2017.7892299
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