4.6 Article

Hip-directed walking-in-place using a single depth camera

期刊

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhcs.2017.03.006

关键词

Walking in place; Virtual locomotion; Navigation control; Virtual environments; Interaction design

资金

  1. Portuguese Foundation for Science and Technology (FCT) through the projects IT-MEDEX [PTDC/EEISH/6038/2014]
  2. TECTON-3D [PTDC/EEI-SII/3154/2012]
  3. CEDAR [PTDC/EIA-EIA/116070/2009]
  4. A-MOP [UTAP-EXPL/QEQ-COM/0019/2014]
  5. FCT [UID/CEC/50021/2013]
  6. Fundação para a Ciência e a Tecnologia [UID/CEC/50021/2013, UTAP-EXPL/QEQ-COM/0019/2014, PTDC/EIA-EIA/116070/2009] Funding Source: FCT

向作者/读者索取更多资源

Walking-in-place (WIP) is a locomotion technique that allows users to travel in virtual environments (VEs) without significantly changing their physical position on the floor. Hip-directed steering(HDS) is a novel physical technique for controlling direction changes in virtual travel using hip movements. We present an WIPbased navigation approach for controlling locomotion in VEs that combines the speed and direction in a scenario similar to a domestic setup in which people interact with a flat screen. Their physical motion data are captured by one depth camera properly aligned with the screen and oriented toward the user. We approach the characteristically noisy data generated by depth cameras via a user study to determine both the range of values and their robustness from the motion data associated with the joints relevant to WIP speed(knee, ankle and foot) and HDS (spine, hip and shoulder) to derive a reliable technique. Our WIP speed method is supported in a simple vocabulary of five different footstep types. Experimental results show that both the knee and hip provide the most robust data. We evaluated our techniques via usability tests exercising common locomotion tasks. The results show that users liked both the speed control and comfort afforded by our speed method. Regarding HDS, users reported that the angular-based method allowed them to travel faster and was both more controllable and easier to learn than the time-based method. Our work shows that a single depth camera can be used to combine locomotion and direction control in a simple and affordable setup.

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