Mapping Surfaces with Earcut

TL;DR

This paper introduces a novel mesh generation approach for shape mapping that considers connectivity as an unknown, enabling robust and simple algorithms for planar shape parameterization and potential volumetric extensions.

Contribution

It presents a new perspective on mesh parameterization by treating connectivity as an unknown and using mesh growth from boundaries, bridging mesh generation and shape mapping.

Findings

Provides a robust algorithm for planar shape mapping with simple topology.

Recovers a weakly visible homotopic domain from boundary inputs.

Discusses challenges and prospects for volumetric map extension.

Abstract

Mapping a shape to some parametric domain is a fundamental tool in graphics and scientific computing. In practice, a map between two shapes is commonly represented by two meshes with same connectivity and different embedding. The standard approach is to input a meshing of one of the two domains plus a function that projects its boundary to the other domain, and then solve for the position of the interior vertices. Inspired by basic principles in mesh generation, in this paper we present the reader a novel point of view on mesh parameterization: we consider connectivity as an additional unknown, and assume that our inputs are just two boundaries that enclose the domains we want to connect. We compute the map by simultaneously growing the same mesh inside both shapes.This change in perspective allows us to recast the parameterization problem as a mesh generation problem, granting access to a wide set of mature tools that are typically not used in this setting. Our practical outcome is a provably robust yet trivial to implement algorithm that maps any planar shape with simple topology to a homotopic domain that is weakly visible from an inner convex kernel. Furthermore, we speculate on a possible extension of the proposed ideas to volumetric maps, listing the major challenges that arise. Differently from prior methods, for which we show that a volumetric extension is not possible, our analysis leaves us reasoneable hopes that the robust generation of volumetric maps via compatible mesh generation could be obtained in the future.