混合现实界面的上下文感知在线适应

David Lindlbauer, A. Feit, Otmar Hilliges
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引用次数: 105

摘要

我们为混合现实(MR)系统提出了一种基于优化的方法,以自动控制何时何地显示应用程序,以及显示多少信息。目前,内容创建者设计应用程序,然后用户手动调整哪些应用程序是可见的,以及它们显示多少信息。每次用户切换上下文时,也就是说,每当他们切换任务或环境时,都必须调整这个选择。由于上下文切换每天发生很多次,我们认为MR接口需要自动化来缓解这个问题。我们提出了一种基于用户当前认知负荷和对其任务和环境的了解的实时方法来自动化这一过程。我们的系统可以调整显示哪些应用程序、显示多少信息以及它们的位置。我们将该问题表述为基于规则的决策和组合优化的混合,可以有效地实时解决。我们提出了一组概念验证应用程序,表明我们的方法适用于广泛的场景。最后,我们在双任务评估中表明,我们的方法减少了36%的次要任务交互。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Context-Aware Online Adaptation of Mixed Reality Interfaces
We present an optimization-based approach for Mixed Reality (MR) systems to automatically control when and where applications are shown, and how much information they display. Currently, content creators design applications, and users then manually adjust which applications are visible and how much information they show. This choice has to be adjusted every time users switch context, i.e., whenever they switch their task or environment. Since context switches happen many times a day, we believe that MR interfaces require automation to alleviate this problem. We propose a real-time approach to automate this process based on users' current cognitive load and knowledge about their task and environment. Our system adapts which applications are displayed, how much information they show, and where they are placed. We formulate this problem as a mix of rule-based decision making and combinatorial optimization which can be solved efficiently in real-time. We present a set of proof-of-concept applications showing that our approach is applicable in a wide range of scenarios. Finally, we show in a dual-task evaluation that our approach decreased secondary tasks interactions by 36%.
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