We present two complementary methods for automatically improving mesh parameterizations and demonstrate that they provide a very desirable combination of efficiency and quality. First, we describe a new iterative method for constructing quasi-conformal parameterizations with free boundaries. We formulate the problem as fitting the coordinate gradients to two guidance vector fields of equal magnitude that are everywhere orthogonal. In only one linear step, our method efficiently generates parameterizations with natural boundaries from those with convex boundaries. If repeated until convergence, it produces the unique global minimizer of the Dirichlet energy. Next, we introduce a new non-linear optimization framework that can rapidly reduce interior distortion under a variety of metrics. By iteratively solving linear systems, our algorithm converges to a high quality, low distortion parameterization in very few iterations. The two components of our system are effective both in combination or when used independently.

Resampling raw surface meshes is one of the most fundamental operations used by nearly all digital geometry processing systems. The vast majority of this work has focused on triangular remeshing, yet quadrilateral meshes are preferred for many surface PDE problems, especially fluid dynamics, and are best suited for defining Catmull-Clark subdivision surfaces. We describe a fundamentally new approach to the quadrangulation of manifold polygon meshes using Laplacian eigenfunctions, the natural harmonics of the surface. These surface functions distribute their extrema evenly across a mesh, which connect via gradient flow into a quadrangular base mesh. An iterative relaxation algorithm simultaneously refines this initial complex to produce a globally smooth parameterization of the surface. From this, we can construct a well-shaped quadrilateral mesh with very few extraordinary vertices. The quality of this mesh relies on the initial choice of eigenfunction, for which we describe algorithms and hueristics to efficiently and effectively select the harmonic most appropriate for the intended application.

We have discovered a fundamentally new approach to the quadrangulation of manifold polygon meshes. First we use Laplacian eigenfunctions, the natural harmonics of the surface, to evenly distribute minima and maxima across a mesh. Then the Morse-Smale complex of this scalar function would give us a quad patch decomposition of the surface by connecting the saddles to the minima and maxima via gradient flow. This patch decomposition is guaranteed to be valid regardless of the genus of the surface. It is also well suited to a semi-regular remeshing of the initial surface into a fully conforming mesh composed exclusively of quadrilaterals.

We propose a new quadrilateral remeshing method for manifolds of arbitrary genus that is at once general, flexible, and efficient. First we compute a smooth harmonic scalar field on the mesh. Given such a field, we compute its gradient field and a second vector field that is everywhere orthogonal to the gradient. We then trace integral lines through these vector fields to sample the mesh. The two nets of integral lines together are used to form the polygons of the output mesh. Our scalar field construction allows users to exercise extensive control over the structure of the final mesh. The entire process is performed without computing an explicit parameterization of the surface, and is thus applicable to manifolds of any genus without the need for cutting.