重新审视莫尔斯-马勒复合物的精确几何学

Son Le Thanh, Michael Ankele, Tino Weinkauf
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引用次数: 0

摘要

莫尔斯-斯马尔复数是可视化数据分析的标准工具。其经典定义基于标量函数梯度的连续视图,其零点为临界点。这些点通过梯度曲线和从鞍点发散出来的曲面连接起来,这些曲面被称为分离矩阵。在离散环境中,莫尔斯-斯马尔复数通常是通过构建假定最陡峭下降方向的组合梯度来提取的。以往的研究表明,这种方法会导致分离矩阵的年龄几何嵌入,而这种嵌入与连续情况下的嵌入会有本质区别。为了实现类似的嵌入,人们提出了构建组合梯度的不同方法。在本文中,我们证明了这些方法会产生不同的拓扑结构,即临界点之间的连通性会发生变化。此外,我们还证明了最陡梯度下降法在应用于某些类型的网格时,可以计算拓扑和几何上精确的莫尔斯-斯马尔复合体。基于这些观察结果,我们提出了一种方法,使在均匀网格上采样的数据的莫尔斯-斯马尔复合体既能达到几何精度,又能达到拓扑精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Revisiting Accurate Geometry for Morse-Smale Complexes
The Morse-Smale complex is a standard tool in visual data analysis. The classic definition is based on a continuous view of the gradient of a scalar function where its zeros are the critical points. These points are connected via gradient curves and surfaces emanating from saddle points, known as separatrices. In a discrete setting, the Morse-Smale complex is commonly extracted by constructing a combinatorial gradient assuming the steepest descent direction. Previous works have shown that this method results in a geometric embedding of the separatrices that can be fundamentally different from those in the continuous case. To achieve a similar embedding, different approaches for constructing a combinatorial gradient were proposed. In this paper, we show that these approaches generate a different topology, i.e., the connectivity between critical points changes. Additionally, we demonstrate that the steepest descent method can compute topologically and geometrically accurate Morse-Smale complexes when applied to certain types of grids. Based on these observations, we suggest a method to attain both geometric and topological accuracy for the Morse-Smale complex of data sampled on a uniform grid.
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