TY - GEN
T1 - Virtual Reality-Based Gymnastics Visualization Using Real-Time Motion Capture Suit
AU - Artlip, Michael
AU - Chen, Jiangong
AU - Li, Bin
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Gymnastics imposes great physical and mental stress on its athletes. Whether due to injury, fatigue, or a desire to rest before a competition, gymnasts cannot always practice their skills successfully and safely in training. To account for this, gymnasts often close their eyes and imagine themselves performing their moves to train focus and muscle memory without excessive physical exertion. This paper presents a system that allows gymnasts to take this a step further by controlling a virtual gymnast from the first-person perspective in virtual reality (VR). When operating the system, the user wears a full-body motion capture suit and a VR headset. The user controls a virtual gymnast using gestures tracked by the suit and perceives an immersive virtual environment through the VR headset. To ensure a fruitful user experience, the virtual environment must be immersive and realistic. First, the virtual gymnastics movements must mimic those of real life. Second, the system must have a high image- rendering speed, dropping no lower than 60 frames per second. Third, real-life movements must correspond to virtual movements nearly instantly, so the motion-to-display (MTD) latency should be minimized. In this paper, we demonstrate that the system's virtual gymnastics animations are derived directly from moves performed in real life using motion capture suit. Additionally, the system achieves an average frame rate of 71.46 frames per second and an average MTD latency of 59.31 ms.
AB - Gymnastics imposes great physical and mental stress on its athletes. Whether due to injury, fatigue, or a desire to rest before a competition, gymnasts cannot always practice their skills successfully and safely in training. To account for this, gymnasts often close their eyes and imagine themselves performing their moves to train focus and muscle memory without excessive physical exertion. This paper presents a system that allows gymnasts to take this a step further by controlling a virtual gymnast from the first-person perspective in virtual reality (VR). When operating the system, the user wears a full-body motion capture suit and a VR headset. The user controls a virtual gymnast using gestures tracked by the suit and perceives an immersive virtual environment through the VR headset. To ensure a fruitful user experience, the virtual environment must be immersive and realistic. First, the virtual gymnastics movements must mimic those of real life. Second, the system must have a high image- rendering speed, dropping no lower than 60 frames per second. Third, real-life movements must correspond to virtual movements nearly instantly, so the motion-to-display (MTD) latency should be minimized. In this paper, we demonstrate that the system's virtual gymnastics animations are derived directly from moves performed in real life using motion capture suit. Additionally, the system achieves an average frame rate of 71.46 frames per second and an average MTD latency of 59.31 ms.
UR - https://www.scopus.com/pages/publications/85146114335
UR - https://www.scopus.com/inward/citedby.url?scp=85146114335&partnerID=8YFLogxK
U2 - 10.1109/MASS56207.2022.00112
DO - 10.1109/MASS56207.2022.00112
M3 - Conference contribution
AN - SCOPUS:85146114335
T3 - Proceedings - 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2022
SP - 728
EP - 729
BT - Proceedings - 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2022
Y2 - 20 October 2022 through 22 October 2022
ER -