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Hand-adaptive user interface: improved gestural interaction in virtual reality

机译:手部自适应用户界面:改进虚拟现实中的手势交互

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Abstract Most interactive user interfaces (UIs) for virtual reality (VR) applications are based on the traditional eye-centred UI design principle, which primarily considers the user’s visual searching efficiency and comfort, but the hand operation performance and ergonomics are relatively less considered. As a result, the hand interaction in VR is often criticized as being less efficient and precise. In this paper, the user’s arm movement features, such as the choice of the hand being used and hand interaction position, are hypothesized to influence the interaction results derived from a VR study. To verify this, we conducted a free hand target selection experiment with 24 participants. The results showed that (a) the hand choice had a significant effect on the target selection results: for a left hand interaction, the targets located in spaces to the left were selected more efficiently and accurately than those in spaces to the right; however, in a right hand interaction, the result was reversed, and (b) the free hand interactions at lower positions were more efficient and accurate than those at higher positions. Based on the above findings, this paper proposes a hand-adaptive UI technique to improve free hand interaction performance in VR. A comprehensive comparison between the hand-adaptive UI and traditional eye-centred UI was also conducted. It was shown that the hand-adaptive UI resulted in a higher interaction efficiency and a lower physical exertion and perceived task difficulty than the traditional UI.
机译:摘要 虚拟现实(VR)应用的交互式用户界面(UI)大多基于传统的以眼睛为中心的UI设计原则,主要考虑用户的视觉搜索效率和舒适度,而对手部操作性能和人体工程学的考虑相对较少。因此,VR中的手部交互经常被批评为效率和精确度较低。在本文中,假设用户的手臂运动特征,例如正在使用的手的选择和手部交互位置,以影响从VR研究中得出的交互结果。为了验证这一点,我们对 24 名参与者进行了自由手目标选择实验。结果表明:(a)手部选择对目标选择结果有显著影响:在左手交互中,左侧空间中的目标选择比右侧空间中的目标选择更有效、更准确;然而,在右手交互中,结果是相反的,(b)低位置的自由手交互比高位置的自由手交互更有效和准确。基于上述发现,本文提出了一种手部自适应UI技术,以提高VR中的手部交互性能。还对手部自适应UI和传统的以眼睛为中心的UI进行了全面比较。结果表明,与传统UI相比,手部自适应UI具有更高的交互效率,更低的体力消耗和感知任务难度。

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