一种边缘保持、数据相关的分层绘制三角剖分方案

James C. Barnes, B. Hamann, K. Joy
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引用次数: 4

摘要

在许多应用中,人们关心的是给定数据点的有限集合中函数的近似和相关的函数值。我们描述了在不同细节水平上近似给定数据的三角测量层次结构。通过考虑中间三角测量的近似误差,可以将其与层次结构的特定级别相关联。针对平面上的多值分散数据,提出了一种新的基于数据的三角剖分方案。我们执行分段线性逼近基于数据相关的三角。我们的方案通过在边缘附近放置顶点来保留在给定数据集中可能存在的边缘(不连续点)。我们首先对给定数据点的凸壳进行粗略的、与数据相关的三角剖分,然后对三角形进行细分,直到三角剖分所隐含的分段线性近似的误差小于某个公差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Edge-Preserving, Data-Dependent Triangulation Scheme for Hierarchical Rendering
In many applications one is concerned with the approximation of functions from a finite set of given data sites with associated function values. We describe a construction of a hierarchy of triangulations which approximate the given data at varying levels of detail. Intermediate triangulations can be associated with a particular level of the hierarchy by considering their approximation errors. This paper presents a new data-dependent triangulation scheme for multi-valued scattered data in the plane. We perform piecewise linear approximation based on data-dependent triangulations. Our scheme preserves edges (discontinuities) that might exist in a given data set by placing vertices close to edges. We start with a coarse, data-dependent triangulation of the convex hull of the given data sites and subdivide triangles until the error of the piecewise linear approximation implied by a triangulation is smaller than some tolerance.
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