Interactive 3D Force‐Directed Edge Bundling
Interactive 3D Force‐Directed Edge Bundling
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DOI：
10.1111/cgf.12881
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发表时间：
2016-06
影响因子：
2.5
通讯作者：
Daniel Zielasko;B. Weyers;B. Hentschel;T. Kuhlen
中科院分区：
文献类型：
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作者：
Daniel Zielasko;B. Weyers;B. Hentschel;T. Kuhlen
3D关系数据的交互式分析具有挑战性。表示此类数据的一种常见方法是节点链接图，因为它们支持分析师实现数据的心理模型。然而，复杂图形的简单3D布局往往在视觉上混乱，甚至比2D布局更混乱。这使得图形探索和数据分析的效率降低。这个问题可以通过边缘捆绑来解决。我们介绍了一种基于3D聚类的边缘捆绑算法，该算法受到力导向边缘捆绑（FDEB）算法[ HvW09b ]的启发，并满足嵌入空间数据分析交互式框架的要求。它是并行化的，并根据运行时的图形大小进行缩放。此外，它还维护了边的模型，从而支持以不同的结构样式渲染图形。我们证明了这一点，从一个猕猴大脑的功能模拟图。
Interactive analysis of 3D relational data is challenging. A common way of representing such data are node‐link diagrams as they support analysts in achieving a mental model of the data. However, naïve 3D depictions of complex graphs tend to be visually cluttered, even more than in a 2D layout. This makes graph exploration and data analysis less efficient. This problem can be addressed by edge bundling. We introduce a 3D cluster‐based edge bundling algorithm that is inspired by the force‐directed edge bundling (FDEB) algorithm [ HvW09b ] and fulfills the requirements to be embedded in an interactive framework for spatial data analysis. It is parallelized and scales with the size of the graph regarding the runtime. Furthermore, it maintains the edge's model and thus supports rendering the graph in different structural styles. We demonstrate this with a graph originating from a simulation of the function of a macaque brain.