Personal Augmented Reality for Information Visualization on Large Interactive Displays
Personal Augmented Reality for Information Visualization on Large Interactive Displays
复制标题
用于大型交互式显示器上信息可视化的个人增强现实
DOI：
10.1109/tvcg.2020.3030460
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发表时间：
2020-09
影响因子：
5.2
通讯作者：
Patrick Reipschläger;Tamara Flemisch;Raimund Dachselt
中科院分区：
文献类型：
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作者：
Patrick Reipschläger;Tamara Flemisch;Raimund Dachselt
在这项工作中，我们提出了大型交互式显示器与个人头戴式增强现实（AR）的信息可视化相结合，以促进数据的探索和分析。尽管大型显示器提供了更多的显示空间，但它们在感知、有效的多用户支持以及管理数据密度和复杂性方面具有挑战性。为了解决这些问题并说明我们提出的设置，我们贡献了一个广泛的设计空间，首先包括AR空间中显示，可视化和对象的空间对齐。接下来，我们讨论可视化的哪些部分可以增强。最后，我们分析了如何使用AR来显示个人视图，以显示额外的信息，并最大限度地减少数据分析师的相互干扰。基于这个概念的基础上，我们提出了一些示例性的技术扩展与AR可视化，并讨论他们的关系，我们的设计空间。我们进一步描述了这些技术如何解决典型的可视化问题，我们已经确定在我们的文献研究。为了研究我们的概念，我们介绍了一个通用的AR可视化框架以及实现几个示例技术的原型。为了展示它们的潜力，我们进一步提出了一个用例演练，在其中我们分析了一个电影数据集。从这些经验中，我们得出结论，贡献的技术可以是有用的，在探索和理解多元数据。我们相信，使用AR扩展大型显示器以实现信息可视化，在数据分析和意义构建方面具有巨大的潜力。
In this work we propose the combination of large interactive displays with personal head-mounted Augmented Reality (AR) for information visualization to facilitate data exploration and analysis. Even though large displays provide more display space, they are challenging with regard to perception, effective multi-user support, and managing data density and complexity. To address these issues and illustrate our proposed setup, we contribute an extensive design space comprising first, the spatial alignment of display, visualizations, and objects in AR space. Next, we discuss which parts of a visualization can be augmented. Finally, we analyze how AR can be used to display personal views in order to show additional information and to minimize the mutual disturbance of data analysts. Based on this conceptual foundation, we present a number of exemplary techniques for extending visualizations with AR and discuss their relation to our design space. We further describe how these techniques address typical visualization problems that we have identified during our literature research. To examine our concepts, we introduce a generic AR visualization framework as well as a prototype implementing several example techniques. In order to demonstrate their potential, we further present a use case walkthrough in which we analyze a movie data set. From these experiences, we conclude that the contributed techniques can be useful in exploring and understanding multivariate data. We are convinced that the extension of large displays with AR for information visualization has a great potential for data analysis and sense-making.