Skip to main navigation Skip to search Skip to main content

Geometry-aware domain decomposition for T-spline-based manifold modeling

  • Hongyu Wang*
  • , Ying He
  • , Xin Li
  • , Xianfeng Gu
  • , Hong Qin
  • *Corresponding author for this work
  • Stony Brook University
  • Nanyang Technological University
  • Louisiana State University

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a new and effective method to construct manifold T-splines of complicated topology/geometry. The fundamental idea of our novel approach is the geometry-aware object segmentation, by which an arbitrarily complicated surface model can be decomposed into a group of disjoint components that comprise branches, handles, and base patches. Such a domain decomposition simplifies objects of arbitrary topological type into a family of genus-zero/one open surfaces, each of which can be conformally parameterized into a set of rectangles. In contrast to the conventional decomposition approaches, our method can guarantee that the cutting locus are consistent on the parametric domain. As a result, the resultant T-splines of decomposed components are automatically glued and have high-order continuity everywhere except at the extraordinary points. We show that the number of extraordinary points of the domain manifold is bounded by the number of segmented components. Furthermore, the entire mesh-to-spline data conversion pipeline can be implemented with full automation, and thus, has potential in shape modeling and reverse engineering applications of complicated real-world objects.

Original languageEnglish
Pages (from-to)359-368
Number of pages10
JournalComputers and Graphics
Volume33
Issue number3
DOIs
StatePublished - Jun 2009
Externally publishedYes

Keywords

  • Manifold splines
  • Object segmentation
  • Shape computing
  • Shape modeling
  • Solid modeling
  • T-Splines
  • Tensor-product B-splines

Fingerprint

Dive into the research topics of 'Geometry-aware domain decomposition for T-spline-based manifold modeling'. Together they form a unique fingerprint.

Cite this