The presence of fully-occluded targets is common within virtual environments, ranging from a virtual object located behind a wall to a datapoint of interest hidden in a complex visualization. However, efficient input techniques for locating and selecting these targets are mostly underexplored in virtual reality (VR) systems. In this paper, we developed an initial set of seven techniques techniques for fully-occluded target selection in VR. We then evaluated their performance in a user study and derived a set of design implications for simple and more complex tasks from our results. Based on these insights, we refined the most promising techniques and conducted a second, more comprehensive user study. Our results show how factors, such as occlusion layers, target depths, object densities, and the estimation of target locations, can affect technique performance. Our findings from both studies and distilled recommendations can inform the design of future VR systems that offer selections for fully-occluded targets.

中文翻译：

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虚拟现实中完全封闭的目标选择

在虚拟环境中，完全被遮挡的目标的存在很常见，范围从墙后的虚拟对象到复杂可视化中隐藏的感兴趣的数据点。但是，在虚拟现实（VR）系统中，用于定位和选择这些目标的有效输入技术大多未得到开发。在本文中，我们开发了一套用于VR中完全封闭目标选择的七种技术。然后，我们在用户研究中评估了它们的性能，并从结果中得出了对简单和更复杂任务的一系列设计含义。基于这些见解，我们优化了最有前途的技术，并进行了第二次更全面的用户研究。我们的结果显示了诸如遮挡层，目标深度，物体密度以及目标位置估算等因素如何，会影响技术性能。我们的研究结果和提炼的建议都可以为将来的VR系统设计提供参考，从而为完全封闭的目标提供选择。