时变模糊轮廓树

A. Lohfink, Frederike Gartzky, Florian Wetzels, Luisa Vollmer, C. Garth
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引用次数: 3

摘要

我们提出了一种基于模糊轮廓树的空间时间序列数据整体拓扑可视化技术。时间相关标量场的常用分析方法识别和跟踪特定特征。为了对数据进行更全面的概述,我们将模糊轮廓树从多个标量场拓扑的可视化和同时分析扩展到时间相关的标量场。由此产生的时变模糊轮廓树允许不需要连续的多个时间步长的比较。我们提供了特定的交互和导航可能性,除了在所有时间步骤上的轮廓树的行为之外,还允许探索单个时间步骤和时间窗口。为了实现这一目标,我们将现有的对齐减少到多个子对齐,并调整模糊轮廓树布局以持续反映子对齐中的变化和相似性。我们将时变模糊轮廓树应用于不同的现实世界数据集,并证明了它们的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time-Varying Fuzzy Contour Trees
We present a holistic, topology-based visualization technique for spatial time series data based on an adaptation of Fuzzy Contour Trees. Common analysis approaches for time dependent scalar fields identify and track specific features. To give a more general overview of the data, we extend Fuzzy Contour Trees, from the visualization and simultaneous analysis of the topology of multiple scalar fields, to time dependent scalar fields. The resulting time-varying Fuzzy Contour Trees allow the comparison of multiple time steps that are not required to be consecutive. We provide specific interaction and navigation possibilities that allow the exploration of individual time steps and time windows in addition to the behavior of the contour trees over all time steps. To achieve this, we reduce an existing alignment to multiple sub-alignments and adapt the Fuzzy Contour Tree-layout to continuously reflect changes and similarities in the sub-alignments. We apply time-varying Fuzzy Contour Trees to different real-world data sets and demonstrate their usefulness.
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