Anisotropic triangulations via discrete Riemannian Voronoi diagrams

International audienceThe construction of anisotropic triangulations is desirable for various applications, such as the numerical solving of partial differential equations and the representation of surfaces in graphics. To solve this notoriously difficult problem in a practical way, we introduce the discrete Riemannian Voronoi diagram, a discrete structure that approximates the Riemannian Voronoi diagram. This structure has been implemented and was shown to lead to good triangulations in R2 and on surfaces embedded in R3 as detailed in our experimental companion paper. In this paper, we study theoretical aspects of our structure. Given a finite set of points P in a domain Ω equipped with a Riemannian metric, we compare the discrete Riemannian Voronoi diagram of P to its Riemannian Voronoi diagram. Both diagrams have dual structures called the discrete Riemannian Delaunay and the Riemannian Delaunay complex. We provide conditions that guarantee that these dual structures are identical. It then follows from previous results that the discrete Riemannian Delaunay complex can be embedded in Ω under sufficient conditions, leading to an anisotropic triangulation with curved simplices. Furthermore, we show that, under similar conditions, the simplices of this triangulation can be straightened

Bregman Voronoi Diagrams: Properties, Algorithms and Applications

The Voronoi diagram of a finite set of objects is a fundamental geometric structure that subdivides the embedding space into regions, each region consisting of the points that are closer to a given object than to the others. We may define many variants of Voronoi diagrams depending on the class of objects, the distance functions and the embedding space. In this paper, we investigate a framework for defining and building Voronoi diagrams for a broad class of distance functions called Bregman divergences. Bregman divergences include not only the traditional (squared) Euclidean distance but also various divergence measures based on entropic functions. Accordingly, Bregman Voronoi diagrams allow to define information-theoretic Voronoi diagrams in statistical parametric spaces based on the relative entropy of distributions. We define several types of Bregman diagrams, establish correspondences between those diagrams (using the Legendre transformation), and show how to compute them efficiently. We also introduce extensions of these diagrams, e.g. k-order and k-bag Bregman Voronoi diagrams, and introduce Bregman triangulations of a set of points and their connexion with Bregman Voronoi diagrams. We show that these triangulations capture many of the properties of the celebrated Delaunay triangulation. Finally, we give some applications of Bregman Voronoi diagrams which are of interest in the context of computational geometry and machine learning.Comment: Extend the proceedings abstract of SODA 2007 (46 pages, 15 figures

Discretized Riemannian Delaunay Triangulations

Anisotropic meshes are desirable for various applications, such as the numerical solving of partial differential equations and graphics.In this report, we introduce an algorithm to compute discrete approximations of Riemannian Voronoi diagrams on 2-manifolds.This is not straightforward because geodesics, shortest paths between points, and therefore distances cannot, in general, be computed exactly.We give conditions that guarantee that our discrete Riemannian Voronoi diagram is combinatorially equivalent to the exact Riemannian Voronoi diagram.This allows us to build upon recent theoretical results on Riemannian Delaunay triangulations, and guarantee that the dual of our discrete Riemannian Voronoi diagram is an embedded triangulation using both approximate geodesics and straight edges.Our implementation employs recent developments in the numerical computation of geodesic distances.We observe that, in practice, our discrete Voronoi Diagram is correct in a far wider range of settings than our theoretical bounds imply.Both the theoretical guarantees on the approximation of the Voronoi diagram and the implementation are new and provides a step towards the practical application of Riemannian Delaunay triangulations.Les maillages anisotropes sont désirables pour de nombreuses applications, telles que la résolution numérique d'équations aux dérivées partielles ou la visualisation.Dans ce rapport, nous présentons un algorithme qui permet de calculer une approximation discrète d'un diagramme de Voronoi Riemannien sur une 2-variété.Il s'agit d'une tache complexe car ce diagramme est basé sur la notion de courbe géodésique, qui ne peut en général pas être calculée de manière exacte.Nous donnons dans ce rapport des conditions qui garantissent que notre diagramme de Voronoi Riemannien discret est combinatoirement équivalent au diagramme de Voronoi Riemannien exact.Ceci nous permet ensuite d'utiliser des résultats récents sur les triangulations de Delaunay Riemanniennes pour garantir le fait que le dual de notre diagramme de Voronoi Riemannien discret est une triangulation plongée, à la fois en utilisant des arêtes géodésiques et des arêtes droites.Notre implémentation est basée sur de récentes avancées dans le calcul numérique des distances géodésiques.Nous observons en pratique que notre diagramme de Voronoi Riemannien discret est correct dans des conditions beaucoup moins contraignantes que ce que notre théorie implique.Les garanties théoriques et l'approximation du diagramme de Voronoi sont nouvelles et sont une étape de plus vers une utilisation pratique des triangulations de Delaunay Riemanniennes

Constructing Intrinsic Delaunay Triangulations of Submanifolds

We describe an algorithm to construct an intrinsic Delaunay triangulation of a smooth closed submanifold of Euclidean space. Using results established in a companion paper on the stability of Delaunay triangulations on $\delta$-generic point sets, we establish sampling criteria which ensure that the intrinsic Delaunay complex coincides with the restricted Delaunay complex and also with the recently introduced tangential Delaunay complex. The algorithm generates a point set that meets the required criteria while the tangential complex is being constructed. In this way the computation of geodesic distances is avoided, the runtime is only linearly dependent on the ambient dimension, and the Delaunay complexes are guaranteed to be triangulations of the manifold

A curvature-adapted anisotropic surface remeshing method

We present a new method for remeshing surfaces that respect the intrinsic anisotropy of the surfaces. In particular, we use the normal informations of the surfaces, and embed the surfaces into a higher dimensional space (here we use 6d). This allow us to form an isotropic mesh optimization problem in this embedded space. Starting from an initial mesh of a surface, we optimize the mesh by improving the mesh quality measured in the embedded space. The mesh is optimized by combining common local modifications operations, i.e., edge flip, edge contraction, vertex smoothing, and vertex insertion. All operations are applied directly on the 3d surface mesh. This method results a curvature-adapted mesh of the surface. This method can be easily adapted to mesh multi-patches surfaces, i.e., containing corner singularities and sharp features. We present examples of remeshed surfaces from implicit functions and CAD models

Computing a high-dimensional euclidean embedding from an arbitrary smooth riemannian metric

International audienceThis article presents a new method to compute a self-intersection free high-dimensional Euclidean embedding (SIFHDE) for surfaces and volumes equipped with an arbitrary Riemannian metric. It is already known that given a high-dimensional (high-d) embedding, one can easily compute an anisotropic Voronoi diagram by back-mapping it to 3D space. We show here how to solve the inverse problem, i.e., given an input metric, compute a smooth intersection-free high-d embedding of the input such that the pullback metric of the embedding matches the input metric. Our numerical solution mechanism matches the deformation gradient of the 3D → higher-d mapping with the given Riemannian metric. We demonstrate applications of the method, by being used to construct anisotropic Restricted Voronoi Diagram (RVD) and anisotropic meshing, that are otherwise extremely difficult to compute. In the SIFHDE-space constructed by our algorithm, difficult 3D anisotropic computations are replaced with simple Euclidean computations, resulting in an isotropic RVD and its dual mesh on this high-d embedding. The results are compared with the state-ofthe-art in anisotropic surface and volume meshings using several examples and evaluation metrics