快速等高轮廓,提高交互性

C. Bajaj, Valerio Pascucci, D. Schikore
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引用次数: 200

摘要

我们提出了一种等等值线算法,该算法对于大数据集中的等等值线的实时交互和修改是近乎最优的。预处理步骤选择被认为是种子细胞的细胞子集S。给定一个特定的等值线,使用高性能范围搜索提取S中与给定等值线相交的所有细胞。使用快速等轮廓传播算法扫描出每个连接的组件。种子点选择和等轮廓传播重复作用的计算复杂度为O(log n’+k),其中n’为S的大小,k为输出的大小。在最坏的情况下,n'=O(n),其中n是单元数,而在实际情况下,n'比n小一到两个数量级。本文描述了凸复合体的种子集构造的一般情况,以及适用于规则拓扑网格(包括直线和曲线网格)的专门算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast isocontouring for improved interactivity
We present an isocontouring algorithm which is near-optimal for real-time interaction and modification of isovalues in large datasets. A preprocessing step selects a subset S of the cells which are considered as seed cells. Given a particular isovalue, all cells in S which intersect the given isocontour are extracted using a high-performance range search. Each connected component is swept out using a fast isocontour propagation algorithm. The computational complexity for the repeated action of seed point selection and isocontour propagation is O(log n'+k), where n' is the size of S and k is the size of the output. In the worst case, n'=O(n), where n is the number of cells, while in practical cases, n' is smaller than n by one to two orders of magnitude. The general case of seed set construction for a convex complex of cells is described, in addition to a specialized algorithm suitable for meshes of regular topology, including rectilinear and curvilinear meshes.
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