Planar Minimization Diagrams via Subdivision with Applications to Anisotropic Voronoi Diagrams

Let X = {f₁, …, f_n} be a set of scalar functions of the form f_i : ?² → ? which satisfy some natural properties. We describe a subdivision algorithm for computing a clustered ε‐isotopic approximation of the minimization diagram of X. By exploiting soft predicates and clustering of Voronoi vertices, our algorithm is the first that can handle arbitrary degeneracies in X, and allow scalar functions which are piecewise smooth, and not necessarily semi‐algebraic. We apply these ideas to the computation of anisotropic Voronoi diagram of polygonal sets; this is a natural generalization of anisotropic Voronoi diagrams of point sites, which extends multiplicatively weighted Voronoi diagrams. We implement a prototype of our anisotropic algorithm and provide experimental results.     

Polyline‐sourced Geodesic Voronoi Diagrams on Triangle Meshes

This paper studies the Voronoi diagrams on 2‐manifold meshes based on geodesic metric (a.k.a. geodesic Voronoi diagrams or GVDs), which have polyline generators. We show that our general setting leads to situations more complicated than conventional 2D Euclidean Voronoi diagrams as well as point‐source based GVDs, since a typical bisector contains line segments, hyperbolic segments and parabolic segments. To tackle this challenge, we introduce a new concept, called local Voronoi diagram (LVD), which is a combination of additively weighted Voronoi diagram and line‐segment Voronoi diagram on a mesh triangle. We show that when restricting on a single mesh triangle, the GVD is a subset of the LVD and only two types of mesh triangles can contain GVD edges. Based on these results, we propose an efficient algorithm for constructing the GVD with polyline generators. Our algorithm runs in O(nNlogN) time and takes O(nN) space on an n‐face mesh with m generators, where N = max{m, n}. Computational results on real‐world models demonstrate the efficiency of our algorithm.     

The Hausdorff Voronoi Diagram of Point Clusters in the Plane

We study the Hausdorff Voronoi diagram of point clusters in the plane, a generalization ofVoronoi diagrams based on the Hausdorff distance function. We derive a tight combinatorial bound on the structural complexity of this diagram and present a plane sweep algorithm for its construction. In particular, we show that the size of the Hausdorff Voronoi diagram is (n + m), where n is the number of points on the convex hulls of the given clusters, and m is the number of crucial supporting segments between pairs of crossing clusters. The plane sweep algorithm generalizes the standard plane sweep paradigm for the construction of Voronoi diagrams with the ability to handle disconnected Hausdorff Voronoi regions. The Hausdorff Voronoi diagram finds direct application in the problem of computing the critical area of a VLSI layout, a measure reflecting the sensitivity of the VLSI design to spot defects during manufacturing.     

Region-expansion for the Voronoi diagram of 3D spheres

Given a set of spheres in 3D, constructing its Voronoi diagram in Euclidean distance metric is not easy at all even though many mathematical properties of its structure are known. This Voronoi diagram has been known for many important applications from science and engineering. In this paper, we characterize the Voronoi diagram of spheres in three-dimensional Euclidean space, which is also known as an additively weighted Voronoi diagram, and propose an algorithm to construct the diagram. Starting with the ordinary Voronoi diagram of the centers of the spheres, the proposed region-expansion algorithm constructs the desired diagram by expanding the Voronoi region of each sphere, one after another. We also show that the whole Voronoi diagram of n spheres can be constructed in O(n³) time in the worst case.     

Approximation of Generalized Voronoi Diagrams by Ordinary Voronoi Diagrams

A numerically robust algorithm for the ordinary Voronoi diagrams is applied to the approximation of various types of generalized Voronoi diagrams. The generalized Voronoi diagrams treated here include Voronoi diagrams for figures, additively weighted Voronoi diagrams, Voronoi diagrams in a river, Voronoi diagrams in a Riemannian plane, and Voronoi diagrams with respect to collision-avoiding shortest paths. The construction of these generalized Voronoi diagrams is reduced to the construction of the ordinary Voronoi diagrams. The methods proposed here can save much time which is otherwise necessary for writing a computer program for each type of generalized Voronoi diagram.     

增删点后的Voronoi 图生成算法

Voronoi 图可广泛应用于模式识别、计算机图形学、计算机辅助设计、地 理信息系统等领域。利用Voronoi 图及其对偶图Delaunay 三角网构建的不规则三角网TIN 能充分地反映地形地貌特征,对TIN 的统一管理和动态调用可较好地应用到数字高程模型 的建立中。通过联机增量和减量算法来来实现增删点后的Voronoi 图的生成,具有能够动态 修改点集、速度快、效率高等优势。     

Euclidean Voronoi diagram of 3D balls and its computation via tracing edges

Despite its important applications in various disciplines in science and engineering, the Euclidean Voronoi diagram for spheres, also known as an additively weighted Voronoi diagram, in 3D space has not been studied as much as it deserves. In this paper, we present an algorithm to compute the Euclidean Voronoi diagram for 3D spheres with different radii. The presented algorithm follows Voronoi edges one by one until the construction is completed in O(mn) time in the worst-case, where m is the number of edges in the Voronoi diagram and n is the number of spherical balls. As building blocks, we show that Voronoi edges are conics that can be precisely represented as rational quadratic Bézier curves. We also discuss how to conveniently represent and process Voronoi faces which are hyperboloids of two sheets.     

分区加权Voronoi图的性质及其面积计算

分区加权Voronoi图是Voronoi图和加权Voronoi图的推广,可以用来模拟移动通信中基站发射天线分扇区以不同功率向周围发射时所覆盖区域的形状。首先,给出了分区加权Voronoi图的性质、定理及相关证明;其次,分析了分区加权Voronoi图中的各种区域,并给出了一种计算相应区域面积的算法;最后,利用分区加权Voronoi图模拟石家庄市部分城区中的基站建设情况,并对模拟产生的重复覆盖、服务区和盲区面积进行了计算。     

关于一般图形Voronoi图的离散构造法的研究

生成元为任意图形的一般图形Vomnoi图，由于其生成元的任意性，使得构造一般图形Voronoi图的算法均比较复杂。本文给出了在生成元边界上选取母点，利用点为生成元的Voronoi图的离散画法进行构造，从而得到一般图形Voronoi图的离散构造法。与其它算法相比，该算法的实现与生成元的形状无关，无需复杂计算，无需考虑误差控制，因而更加实用，效率也更高。实验结果表明，该算法简单，具有较高的理论价值和应用价值。     

On 2-Site Voronoi Diagrams Under Geometric Distance Functions

We revisit a new type of Voronoi diagram, in which distance is measured from a point to a pair of points. We consider a few more such distance functions, based on geometric primitives, namely, circles and triangles, and analyze the structure and complexity of the nearest- and furthest-neighbor 2-site Voronoi diagrams of a point set in the plane with respect to these distance functions. In addition, we bring to notice that 2-point site Voronoi diagrams can be alternatively interpreted as 1-site Voronoi diagrams of segments, and thus, our results also enhance the knowledge on the latter.     

Delaunay meshing of isosurfaces

We present an isosurface meshing algorithm, DelIso, based on the Delaunay refinement paradigm. This paradigm has been successfully applied to mesh a variety of domains with guarantees for topology, geometry, mesh gradedness, and triangle shape. A restricted Delaunay triangulation, dual of the intersection between the surface and the three-dimensional Voronoi diagram, is often the main ingredient in Delaunay refinement. Computing and storing three-dimensional Voronoi/Delaunay diagrams become bottlenecks for Delaunay refinement techniques since isosurface computations generally have large input datasets and output meshes. A highlight of our algorithm is that we find a simple way to recover the restricted Delaunay triangulation of the surface without computing the full 3D structure. We employ techniques for efficient ray tracing of isosurfaces to generate surface sample points, and demonstrate the effectiveness of our implementation using a variety of volume datasets.     

Hadoop下面元加权Voronoi图并行算法及应用

面元加权Voronoi图是生成元为面元的加权Voronoi图。针对大规模数据情况下面元加权Voronoi图存在的计算效率不高问题,结合面元边界点提取方法,提出一种基于Hadoop云平台的面元加权Voronoi图的并行生成算法,进行了单机和集群实验。实验结果表明,算法能有效处理大规模栅格数据,明显提高面元加权Voronoi图的生成速度。还可应用于城市绿地设计规划,为绿地设计提供决策依据。     

基于Voronoi图的无线传感网休眠算法

针对无线传感网络的节点是高密度随机分布在部署区域可能产生重复覆盖而浪费节点和网络整体能量的问题,改进了一种基于Voronoi图的休眠算法。通过计算节点与其邻居节点和其产生的Voronoi图顶点的距离来判断该休眠节点,减少网络的整体能量消耗。仿真结果表明,所改进的休眠算法节约了网络的整体能量,延长了网络的生命周期。     

Exact Computation of the Topology and Geometric Invariants of the Voronoi Diagram of Spheres in 3D

In this paper, we are addressing the exact computation of the Delaunay graph (or quasi-triangulation) and the Voronoi diagram of spheres using Wu’s algorithm. Our main contributions are first a methodology for automated derivation of invariants of the Delaunay empty circumsphere predicate for spheres and the Voronoi vertex of four spheres, then the application of this methodology to get all geometrical invariants that intervene in this problem and the exact computation of the Delaunay graph and the Voronoi diagram of spheres. To the best of our knowledge, there does not exist a comprehensive treatment of the exact computation with geometrical invariants of the Delaunay graph and the Voronoi diagram of spheres. Starting from the system of equations defining the zero-dimensional algebraic set of the problem, we are applying Wu’s algorithm to transform the initial system into an equivalent Wu characteristic (triangular) set. In the corresponding system of algebraic equations, in each polynomial (except the first one), the variable with higher order from the preceding polynomial has been eliminated (by pseudo-remainder computations) and the last polynomial we obtain is a polynomial of a single variable. By regrouping all the formal coefficients for each monomial in each polynomial, we get polynomials that are invariants for the given problem. We rewrite the original system by replacing the invariant polynomials by new formal coefficients. We repeat the process until all the algebraic relationships (syzygies) between the invariants have been found by applying Wu’s algorithm on the invariants. Finally, we present an incremental algorithm for the construction of Voronoi diagrams and Delaunay graphs of spheres in 3D and its application to Geodesy.     

Generating and updating multiplicatively weighted Voronoi diagrams for point,line and polygon features in GIS

A Voronoi diagram is an interdisciplinary concept that has been applied to many fields. In geographic information systems (GIS), existing capabilities for generating Voronoi diagrams normally focus on ordinary (not weighted) point (not linear or area) features. For better integration of Voronoi diagram models and GIS, a raster-based approach is developed, and implemented seamlessly as an ArcGIS extension using ArcObjects. In this paper, the methodology and implementation of the extension are described, and examples are provided for ordinary or weighted point, line, and polygon features. Advantages and limitations of the extensions are also discussed. The extension has the following features: (1) it works for point, line, and polygon vector features; (2) it can generate both ordinary and multiplicatively weighted Voronoi diagrams in vector format; (3) it can assign non-spatial attributes of input features to Voronoi cells through spatial joining; and (4) it can produce an ordinary or a weighted Euclidean distance raster dataset for spatial modeling applications. The results can be conveniently combined with other GIS datasets to support both vector-based spatial analysis and raster-based spatial modeling.     

The optimal centroidal Voronoi tessellations and the gersho's conjecture in the three-dimensional space

Optimal centroidal Voronoi tessellations have important applications in many different areas such as vector quantization, data and image processing, clustering analysis, and resource management. In the three-dimensional Euclidean space, they are also useful to the mesh generation and optimization. In this paper, we conduct extensive numerical simulations to investigate the asymptotic structures of optimal centroidal Voronoi tessellations for a given domain. Such a problem is intimately related to the famous Gersho's conjecture, for which a full proof is still not available. We provide abundant evidence to substantiate the claim of the conjecture: the body-centered-cubic lattice (or Par6) based centroidal Voronoi tessellation has the lowest cost (or energy) per unit volume and is the most likely congruent cell predicted by the three-dimensional Gersho conjecture. More importantly, we probe the various properties of this optimal configuration including its dual triangulations which bear significant consequences in applications to three-dimensional high quality meshing.     

3D hyperbolic Voronoi diagrams

Voronoi diagrams have useful applications in various fields and are one of the most fundamental concepts in computational geometry. Although Voronoi diagrams in the plane have been studied extensively, using different notions of sites and metrics, little is known for other geometric spaces. In this paper, we are interested in the Voronoi diagram of a set of sites in the 3D hyperbolic upper half-space. We first present some introductory results in 3D hyperbolic upper half-space and then give an incremental algorithm to construct Voronoi diagram. Finally, we consider five models of 3D hyperbolic manifolds that are equivalent under isometries. By these isometries we can transform the Voronoi diagram of each model to others.     

Fast Voronoi modeling

The common way to construct Voronoi tessellations is to compare the distances between given reference points using a given distance function. To generalize this distance-function concept we expand an existing approach which defines distance functions by their ``unit circles'. Our new approach allows modeling the ``unit circles' by a closed Spline curve. Changing the control polygon directly affects the tessellation's appearance. Typically generalized Voronoi diagrams are represented by Voronoi vertices and curves separating the individual tiles. To obtain interactive modeling we extended an existing hardware accelerated rendering approach computing a bitmap-representation using different colors for individual tiles. With our extension, we are able to use our Spline distance representations as input for a growing process. This growing process easily takes into account weighting approaches like multiplicative, additive, and even free functional weighting.     

弱非均匀Voronoi图细胞面积／体积的快速近似算法

本文针对弱非均匀Voronoi图,介绍一种计算细胞面积／体积的新型快速近似算法．该算法引入一组或多组“虚拟流场”,利用流体力学连续方程的差分近似,得到Voronoi细胞间的递推关系．该算法的优点是复杂度低,递推公式简单,容易在计算机上实现．通过算例研究了各种情况下的误差大小,采用单虚拟流场已经可以得到可以接受的误差范围,而采用双虚拟流场更能进一步减小此误差．本文的目的旨在提供一个全新的思路,通过连续的微分方程来近似考虑离散的图论问题．