An obstruction to Delaunay triangulations in Riemannian manifolds
نویسندگان
چکیده
Delaunay has shown that the Delaunay complex of a finite set of points P of Euclidean space R triangulates the convex hull of P , provided that P satisfies a mild genericity property. Voronoi diagrams and Delaunay complexes can be defined for arbitrary Riemannian manifolds. However, Delaunay’s genericity assumption no longer guarantees that the Delaunay complex will yield a triangulation; stronger assumptions on P are required. A natural one is to assume that P is sufficiently dense. Although results in this direction have been claimed, we show that sample density alone is insufficient to ensure that the Delaunay complex triangulates a manifold of dimension greater than 2. 1 Delaunay complex and Delaunay triangulation Let (M, dM) be a metric space, and let P be a finite set of points of M. An empty ball is an open ball in the metric dM that contains no point from P . We say that an empty ball B is maximal if no other empty ball with the same centre properly contains B. A Delaunay ball is a maximal empty ball. A simplex σ is a Delaunay simplex if there exists some Delaunay ball B that circumscribes σ, i.e., such that the vertices of σ belong to ∂B ∩ P . The Delaunay complex is the set of Delaunay simplices, and is denoted DelM(P ). It is an abstract simplicial complex and so defines a topological space, |DelM(P )|, called its carrier . We say that DelM(P ) triangulates M if |DelM(P )| is homeomorphic to M. A Delaunay triangulation of M is a homeomorphism H : |DelM(P )| → M. The Voronoi cell associated with p ∈ P is given by VM(p) = {x ∈M | dM(x, p) ≤ dM(x, q) for all q ∈ P}. More generally, a Voronoi face is the intersection of a set of Voronoi cells: given σ = {p0, . . . , pk} ⊂ P , we define the associated Voronoi face as
منابع مشابه
Anisotropic Triangulations via Discrete Riemannian Voronoi Diagrams
The 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 struc...
متن کاملACTION OF SEMISIMPLE ISOMERY GROUPS ON SOME RIEMANNIAN MANIFOLDS OF NONPOSITIVE CURVATURE
A manifold with a smooth action of a Lie group G is called G-manifold. In this paper we consider a complete Riemannian manifold M with the action of a closed and connected Lie subgroup G of the isometries. The dimension of the orbit space is called the cohomogeneity of the action. Manifolds having actions of cohomogeneity zero are called homogeneous. A classic theorem about Riemannian manifolds...
متن کاملDelaunay Triangulation of Manifolds
We present an algorithmic framework for producing Delaunay triangulations of manifolds. The input to the algorithm is a set of sample points together with coordinate patches indexed by those points. The transition functions between nearby coordinate patches are required to be bi-Lipschitz with a constant close to 1. The primary novelty of the framework is that it can accommodate abstract manifo...
متن کاملConstructing 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 δ-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 in...
متن کاملA Geometry Preserving Kernel over Riemannian Manifolds
Abstract- Kernel trick and projection to tangent spaces are two choices for linearizing the data points lying on Riemannian manifolds. These approaches are used to provide the prerequisites for applying standard machine learning methods on Riemannian manifolds. Classical kernels implicitly project data to high dimensional feature space without considering the intrinsic geometry of data points. ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Discrete & Computational Geometry
دوره 59 شماره
صفحات -
تاریخ انتشار 2018