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Evaluation of Body-centric Locomotion with Different Transfer Functions in Virtual Reality

机译:对虚拟现实中不同传递函数的身体主体运动的评估

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Body-centric locomotion allows users to navigate virtual environments with body parts (e.g. head tilt, arm swing or torso lean). Transfer functions are an important determinant of the locus of such a locomotion method. However, there is little known about the effects of transfer functions on virtual locomotion with different body parts. In this work, we selected four typical transfer functions (linear function: L, power function: P, a piecewise function with constant and linear functions: CL, and a piecewise function with constant and power functions: CP) and four body parts (head, arm, torso, and knee) from existing works, and conducted an experiment to evaluate their effects on virtual locomotion under three distances (5, 10, and 15 m) in Virtual Reality (VR). Results show that (1) CP function generally led to the longest task time with a low rate of failed trials, while CL function had the shortest task time with a high rate of failed trials; (2) body parts significantly affected the rate of failed trials, but not task time and final position offset. Head and torso resulted in the lowest and highest rate of failed trials respectively; (3) body parts did not differ in User Experience Questionnaire-Short (UEQ-S), UEQ-S Pragmatic and UEQ-S Hedonic. L was rated as the highest score for UEQ-S, UEQ-S Pragmatic and UEQ-S Hedonic, but CP had the lowest score. According to the results, we provide implications of designing body-centric locomotion with different transfer functions in VR.
机译:以身体为中心的机器允许用户使用身体部位导航虚拟环境(例如,头部倾斜,臂摇摆或躯干瘦)。转移功能是这种运动方法的基因座的重要决定因素。然而,关于具有不同身体部位的虚拟运动的传递函数的影响几乎不知道。在这项工作中,我们选择了四个典型的传输功能(线性函数:L,功率功能:P,具有恒定和线性功能的分段功能:CL,以及具有恒定和功率功能的分段功能:CP)和四个身体部位(头部来自现有作品的手臂,躯干和膝关节,并进行了实验,以评估虚拟现实(VR)中的三个距离(5,10和15米)下的虚拟运动的影响。结果表明(1)CP功能一般导致了失败的试验速率低的最长任务时间,而CL功能具有最短的任务时间,试验失败的速度很高; (2)身体部位显着影响失败的试验速度,但不是任务时间和最终位置偏移。头部和躯干分别导致了最低和最高的试验率; (3)身体部位在用户体验问卷 - 短(UEQ-S),UEQ-S务实和UEQ-S Hedonic中没有差异。 L被评为UEQ-S,UEQ-S务实和UEQ-S Hedonic的最高分,但CP得分最低。根据结果​​,我们提供了在VR中使用不同传递函数设计以与不同的传递函数为中心的机器人的影响。

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