论文标题
时间轴设计空间,用于对时变空间3D数据的沉浸式探索
Timeline Design Space for Immersive Exploration of Time-Varying Spatial 3D Data
论文作者
论文摘要
时间表是代表和操纵时间数据的常见可视化,从历史事件讲故事到动画创作。但是,时间轴可视化很少会直接考虑时空3D数据(例如网格或体积模型),通常使用3D可视化器一次仅显示一个时间步长探索。在本文中,利用虚拟现实的工作空间和3D相互作用功能的增加,我们建议使用时间表可视化3D时间数据来支持探索和分析。首先,我们为3D时间数据提出了一个时间表设计空间,该空间扩展了Brehmer等人提出的时间表设计空间。所提出的设计空间适应了比例,布局和表示尺寸,以说明深度维度以及如何分区和结构化3D时间数据。在我们的方法中,引入了一个额外的维度,即支持,这进一步表征了可视化的3D维度。为了补充VR系统的设计空间和相互作用功能,我们讨论了3D时间表有效可视化所需的相互作用方法。然后,为了评估3D时间表的好处,我们进行了正式的评估,并具有两个主要目标:将提出的可视化与传统的可视化方法进行比较;探索用户如何与不同的3D时间轴设计互动。我们的结果表明,使用时间表可以更舒适地实现与时间相关的任务,并且对于需要分析周围时间上下文的特定任务,可以更有效地实现。尽管不同的时间表设计之间的比较尚无定论,但参与者报告说,对时间轴设计的明确偏爱没有占据垂直空间。最后,我们说明了3D时间表与实际用例的使用在生物3D颞型数据集的分析中。
Timelines are common visualizations to represent and manipulate temporal data, from historical events storytelling to animation authoring. However, timeline visualizations rarely consider spatio-temporal 3D data (e.g. mesh or volumetric models) directly, which are typically explored using 3D visualizers only displaying one time-step at a time. In this paper, leveraging the increased workspace and 3D interaction capabilities of virtual reality, we propose to use timelines for the visualization of 3D temporal data to support exploration and analysis. First, we propose a timeline design space for 3D temporal data extending the timeline design space proposed by Brehmer et al. The proposed design space adapts the scale, layout and representation dimensions to account for the depth dimension and how 3D temporal data can be partitioned and structured. In our approach, an additional dimension is introduced, the support, which further characterizes the 3D dimension of the visualization. To complement the design space and the interaction capabilities of VR systems, we discuss the interaction methods required for the efficient visualization of 3D timelines. Then, to evaluate the benefits of 3D timelines, we conducted a formal evaluation with two main objectives: comparing the proposed visualization with a traditional visualization method; exploring how users interact with different 3D timeline designs. Our results showed that time-related tasks can be achieved more comfortably using timelines, and more efficiently for specific tasks requiring the analysis of the surrounding temporal context. Though the comparison between the different timeline designs were inconclusive, participants reported a clear preference towards the timeline design that did not occupy the vertical space. Finally, we illustrate the use of the 3D timelines to a real use-case on the analysis of biological 3D temporal datasets.