Revealing Structure in Visualizations of Dense 2D and 3D Parallel Coordinates
Revealing Structure in Visualizations of Dense 2D and 3D Parallel Coordinates
复制标题
揭示密集 2D 和 3D 平行坐标可视化中的结构
DOI：
10.1057/palgrave.ivs.9500117
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发表时间：
2006
影响因子：
2.3
通讯作者：
M. Cooper
中科院分区：
文献类型：
--
作者：
J. Johansson;P. Ljung;M. Jern;M. Cooper
平行坐标是用于多变量数据的可视化的公知技术。当数据集的大小增加时，平行坐标显示导致图像过于混乱而无法感知任何结构。我们通过构建高精度纹理来表示数据来解决这个问题。通过使用对高精度纹理进行操作的传递函数，可以突出显示整个数据集或数据簇的不同方面。我们的方法实现在标准的2D平行坐标和3D多关系平行坐标。此外，当可视化更大数量的聚类时，可以通过呈现各种聚类统计来使用称为“特征动画”的技术作为指导。一个案例研究也进行说明分析过程中，使用我们提出的技术分析大型多元数据集。
Parallel coordinates is a well-known technique used for visualization of multivariate data. When the size of the data sets increases the parallel coordinates display results in an image far too cluttered to perceive any structure. We tackle this problem by constructing high-precision textures to represent the data. By using transfer functions that operate on the high-precision textures, it is possible to highlight different aspects of the entire data set or clusters of the data. Our methods are implemented in both standard 2D parallel coordinates and 3D multi-relational parallel coordinates. Furthermore, when visualizing a larger number of clusters, a technique called ‘feature animation’ may be used as guidance by presenting various cluster statistics. A case study is also performed to illustrate the analysis process when analysing large multivariate data sets using our proposed techniques.