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Spatial modeling using triangular, tetrahedral, and pentatopic decompositions.

机译:使用三角,四面体和五边形分解的空间建模。

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摘要

Techniques are described for facilitating operations for spatial modeling using triangular, tetrahedral, and pentatopic decompositions of the underlying domain. In the case of terrain data, techniques are presented for navigating between adjacent triangles of a hierarchical triangle mesh where the triangles are obtained by a recursive quadtree-like subdivision of the underlying space into four equilateral triangles. We describe a labeling technique for the triangles which is useful in implementing the quadtree triangle mesh as a linear quadtree (i.e., a pointer-less quadtree). The navigation can then take place in this linear quadtree. This results in algorithms that have a worst-case constant time complexity, as they make use of a fixed number of bit manipulation operations.; In the case of volumetric data, we consider a multi-resolution representation based on a decomposition of a field domain into nested tetrahedral cells generated by recursive tetrahedron bisection, that we call a Hierarchy of Tetrahedra (HT). We describe our implementation of an HT, and discuss how to extract conforming meshes from an HT so as to avoid discontinuities in the approximation of the associated scalar field. This is accomplished by using worst-case constant time neighbor finding algorithms. We also present experimental results in connection with a set of basic queries for performing analysis of volume data sets at different levels of detail.; In the case of four-dimensional data which can include time as the fourth dimension, we present a multi-resolution representation of a four-dimensional scalar field based on a recursive decomposition of a hypercubic domain into a hierarchy of nested four-dimensional simplexes, that we call a Hierarchy of Pentatopes (HP). This structure allows us to generate conforming meshes that avoid discontinuities in the corresponding approximation of the associated scalar field. Neighbor finding is an important part of this process and using our structure, it is possible to find neighbors in worst-case constant time by using bit manipulation operations, thereby avoiding traversing the hierarchy.
机译:描述了用于使用基础域的三角,四面体和五边形分解来促进空间建模操作的技术。在地形数据的情况下,提出了在分层三角形网格的相邻三角形之间导航的技术,其中这些三角形是通过将基础空间递归四叉树状细分为四个等边三角形来获得的。我们描述了三角形的标记技术,该技术可用于将四叉树三角形网格实现为线性四叉树(即无指针四叉树)。然后可以在此线性四叉树中进行导航。这导致算法使用最坏情况的恒定时间复杂度,因为它们使用固定数量的位操作。在体积数据的情况下,我们考虑基于域域分解为递归四面体二等分生成的嵌套四面体细胞的多分辨率表示,我们称其为四面体层次(HT)。我们描述了HT的实现,并讨论了如何从HT提取符合要求的网格,以避免相关标量场近似中的不连续性。这是通过使用最坏情况的恒定时间邻居发现算法来完成的。我们还提供了与一组基本查询相关的实验结果,这些基本查询用于对不同细节级别的体积数据集进行分析。在可以将时间作为第四维的多维数据的情况下,我们基于超立方域递归分解为嵌套的四维单纯形的层次结构,给出了四维标量场的多分辨率表示,我们称之为五角形层次结构(HP)。这种结构使我们能够生成符合标准的网格,避免相关标量场的近似近似中出现不连续性。邻居查找是此过程的重要组成部分,使用我们的结构,可以通过使用位操作操作在最坏情况下恒定的时间内查找邻居,从而避免遍历层次结构。

著录项

  • 作者

    Lee, Michael Thomas.;

  • 作者单位

    University of Maryland, College Park.;

  • 授予单位 University of Maryland, College Park.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 178 p.
  • 总页数 178
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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