Seamless parametrization with arbitrary cones for arbitrary genus

Marcel Campen, Hanxiao Shen, Jiaran Zhou, Denis Zorin

Research output: Contribution to journalArticlepeer-review

Abstract

Seamless global parametrization of surfaces is a key operation in geometry processing, e.g., for high-quality quad mesh generation. A common approach is to prescribe the parametric domain structure, in particular, the locations of parametrization singularities (cones), and solve a non-convex optimization problem minimizing a distortion measure, with local injectivity imposed through either constraints or barrier terms. In both cases, an initial valid parametrization is essential to serve as a feasible starting point for obtaining an optimized solution. While convexified versions of the constraints eliminate this initialization requirement, they narrow the range of solutions, causing some problem instances that actually do have a solution to become infeasible. We demonstrate that for arbitrary given sets of topologically admissible parametric cones with prescribed curvature, a global seamless parametrization always exists (with the exception of one well-known case). Importantly, our proof is constructive and directly leads to a general algorithm for computing such parametrizations. Most distinctively, this algorithm is bootstrapped with a convex optimization problem (solving for a conformal map), in tandem with a simple linear equation system (determining a seamless modification of this map). This initial map can then serve as a valid starting point and be optimized for low distortion using existing injectivity preserving methods.

Original languageEnglish (US)
Article number2
JournalACM Transactions on Graphics
Volume39
Issue number1
DOIs
StatePublished - Dec 2019

Keywords

  • Cone metric
  • Conformal
  • Holonomy

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design

Fingerprint

Dive into the research topics of 'Seamless parametrization with arbitrary cones for arbitrary genus'. Together they form a unique fingerprint.

Cite this