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Interaction Strategies for Effective Augmented Reality Geo-Visualization: Insights from Spatial Cognition
Human-Computer Interaction ( IF 4.5 ) Pub Date : 2018-10-30 , DOI: 10.1080/07370024.2018.1531001
Aaron L. Gardony 1, 2 , Shaina B. Martis 3 , Holly A. Taylor 1, 3 , Tad T. Brunyé 1, 2, 3
Affiliation  

Standalone augmented reality (AR) systems have great potential for interactive three-dimensional (3D) geo-visualization. Emerging head-worn AR technologies can display rich graphical imagery of large-scale environments and permit intuitive interaction through gestural and voice inputs. Yet, how users engage in geo-visualization through these interfaces and what interaction strategies yield the best spatial memory and navigation performance remain open questions. In the present empirical investigation, we related user interactions in a 3D geo-visualization application implemented on the Microsoft HoloLens AR system to virtual navigation outcomes. Informed by spatial cognitive theory, we uncovered interaction strategies during goal-oriented study of a 3D urban environment that predicted different aspects of navigation performance. Users who positioned the 3D city model to gain an overhead (i.e. survey perspective) view early on performed best when later following the route from memory. In contrast, consistent interaction switching (i.e. perspective transformation) during study predicted navigational efficiency when participants were unexpectedly tasked to return to the origin of the route. Individual differences also related to aspects of user interaction. Implications for 3D geo-visualization and navigation-assistive AR application design and suggestions for future directions are discussed.



中文翻译:

有效增强现实地理可视化的交互策略:来自空间认知的见解

独立增强现实(AR)系统在交互式三维(3D)地理可视化方面具有巨大潜力。新兴的头戴式AR技术可以显示大型环境的丰富图形图像,并允许通过手势和语音输入进行直观的交互。然而,用户如何通过这些界面进行地理可视化以及哪种交互策略可以产生最佳的空间记忆和导航性能仍是悬而未决的问题。在当前的实证研究中,我们将在Microsoft HoloLens AR系统上实现的3D地理可视化应用程序中的用户交互与虚拟导航结果相关联。在空间认知理论的指导下,我们在目标导向的3D城市环境研究中发现了可预测导航性能不同方面的交互策略。定位3D城市模型以尽早获得俯视图(即,勘测视角)的用户在以后遵循从内存出发的路线时表现最佳。相反,研究过程中一致的交互切换(即,透视变换)可预测出乎意料的任务是让参与者返回路线起点时的导航效率。个体差异也与用户交互方面有关。讨论了3D地理可视化和导航辅助AR应用程序设计的含义以及对未来方向的建议。研究中的透视变换)预测了当参与者意外地要返回路线起点时的导航效率。个体差异也与用户交互方面有关。讨论了3D地理可视化和导航辅助AR应用程序设计的含义以及对未来方向的建议。研究中的透视变换)预测了当参与者被意外地任务返回到路线起点时的导航效率。个体差异也与用户交互方面有关。讨论了3D地理可视化和导航辅助AR应用程序设计的含义以及对未来方向的建议。

更新日期:2018-10-30
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