一个用于探索大型虚拟环境的系统,结合了规模化的平移增益和干预

Xianshi Xie, Qiufeng Lin, Haojie Wu, G. Narasimham, T. McNamara, J. Rieser, Bobby Bodenheimer
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引用次数: 40

摘要

本文评估了两种方法的结合,以适应双足运动来探索头戴式显示器(hmd)在有限跟踪空间的限制下显示的虚拟环境。我们结合了一种改变运动光流的方法,有效地缩放平移增益,以及一种干预和操纵用户在物理空间中的位置的方法,同时保留他们对虚拟空间的空间意识。后一种技术称为重置。在两个实验中,我们评估了平移增益的缩放和重置,同时受试者沿着一条路径移动,然后转向面对记忆中的物体。我们发现这两种技术可以有效地结合起来,尽管重置有认知成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A system for exploring large virtual environments that combines scaled translational gain and interventions
This paper evaluates the combination of two methods for adapting bipedal locomotion to explore virtual environments displayed on head-mounted displays (HMDs) within the confines of limited tracking spaces. We combine a method of changing the optic flow of locomotion, effectively scaling the translational gain, with a method of intervening and manipulating a user's locations in physical space while preserving their spatial awareness of the virtual space. This latter technique is called resetting. In two experiments, we evaluate both scaling the translational gain and resetting while a subject locomotes along a path and then turns to face a remembered object. We find that the two techniques can be effectively combined, although there is a cognitive cost to resetting.
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