A faster divide-and-conquer algorithm for constructing delaunay triangulations

An easily implemented modification to the divide-and-conquer algorithm for computing the Delaunay triangulation ofn sites in the plane is presented. The change reduces its Θ(n logn) expected running time toO(n log logn) for a large class of distributions that includes the uniform distribution in the unit square. Experimental evidence presented demonstrates that the modified algorithm performs very well forn≤2¹⁶, the range of the experiments. It is conjectured that the average number of edges it creates—a good measure of its efficiency—is no more than twice optimal forn less than seven trillion. The improvement is shown to extend to the computation of the Delaunay triangulation in theL _p metric for 1<p≤∞.     

Duality of constrained Voronoi diagrams and Delaunay triangulations

We introduce theconstrained Voronoi diagram of a planar straight-line graph containingn vertices or sites where the line segments of the graph are regarded as obstacles, and show that an extended version of this diagram is the dual of theconstrained Delaunay triangulation. We briefly discussO(n logn) algorithms for constructing the extended constrained Voronoi diagram.This work was partially supported by a grant from the Natural Sciences and Engineering Research Council of Canada.     

A note on lee and schachter's algorithm for delaunay triangulation

Lee and Schachter have presented an algorithm for the Delaunay triangulation of a set of points whose convex hull is a rectangular region. An addendum to that algorithm is presented which gives the Delaunay triangulation of a set of points with an arbitrary convex hull. Timing results are also given.     

Two algorithms for constructing a Delaunay triangulation

This paper provides a unified discussion of the Delaunay triangulation. Its geometric properties are reviewed and several applications are discussed. Two algorithms are presented for constructing the triangulation over a planar set ofN points. The first algorithm uses a divide-and-conquer approach. It runs inO(N logN) time, which is asymptotically optimal. The second algorithm is iterative and requiresO(N ²) time in the worst case. However, its average case performance is comparable to that of the first algorithm.This work was supported in part by the National Science Foundation under grant MCS-76-17321 and the Joint Services Electronics Program under contract DAAB-07-72-0259.     

A Note on Point Location in Delaunay Triangulations of Random Points

This short note considers the problem of point location in a Delaunay triangulation of n random points, using no additional preprocessing or storage other than a standard data structure representing the triangulation. A simple and easy-to-implement (but, of course, worst-case suboptimal) heuristic is shown to take expected time O(n ^1/3 ) . Received November 27, 1997; revised February 15, 1998.     

A fixed-parameter tractable algorithm for matrix domination

Matrix domination is the NP-complete problem of determining whether a given {0,1} matrix contains a set of k non-zero entries that are in the same row or same column as all other non-zero entries. Using a kernelization and search tree approach, we show the problem to be fixed-parameter tractable with running time .     

平面点集Delaunay三角剖分的分治算法

为发展图形网格化技术,研究了平面点集的三角剖分算法.根据经典算法中在实际应用中遇到的共性问题,提炼了3个工具算法;为了更好地表示平面区域划分的拓扑信息,引入了双链接边表(DCEL)的数据结构.在此基础上,设计并实现了平面集Delaunay三角剖分分治算法,并对特殊退化情况进行了处理,通过计算表明了该算法时间复杂度为0(N* logN).实验数据结果验证了该算法的正确性、健壮性.     

An in-place algorithm for Klee's measure problem in two dimensions

We present the first in-place algorithm for solving Klee's measure problem for a set of n axis-parallel rectangles in the plane. Our algorithm runs in O(n3/2logn) time and uses O(1) extra words in addition to the space needed for representing the input. The algorithm is surprisingly simple and thus very likely to yield an implementation that could be of practical interest. As a byproduct, we develop an optimal algorithm for solving Klee's measure problem for a set of n intervals; this algorithm runs in optimal time O(nlogn) and uses O(1) extra space.     

A linear-time algorithm for linearL1 approximation of points

In this paper we present a linear-time algorithm for approximating a set ofn points by a linear function, or a line, that minimizes theL ₁ norm. The algorithmic complexity of this problem appears not to have been investigated, although anO(n ³) naive algorithm can be easily obtained based on some simple characteristics of an optimumL ₁ solution. Our linear-time algorithm is optimal within a constant factor and enables us to use linearL ₁ approximation of many points in practice. The complexity ofL ₁ linear approximation of a piecewise linear function is also touched upon.     

A Randomized Algorithm for the Voronoi Diagram of Line Segments on Coarse-Grained Multiprocessors

We present a randomized algorithm for computing the Voronoi diagram of line segments using coarse-grained parallel machines. Operating on P processors, for any input of n line segments, this algorithm performs O((n log n)/P) local operations per processor, O(n/P) messages per processor, and O(1) communication phases, with high probability for n=Ω(P ^3+ε ) . Received June 1, 1997; revised March 10, 1998.     

A divide-and-conquer approach for automatic polycube map construction

Polycube map is a global cross-surface parameterization technique, where the polycube shape can roughly approximate the geometry of modeled objects while retaining the same topology. The large variation of shape geometry and its complex topological type in real-world applications make it difficult to effectively construct a high-quality polycube that can serve as a good global parametric domain for a given object. In practice, existing polycube map construction algorithms typically require a large amount of user interaction for either pre-constructing the polycubes with great care or interactively specifying the geometric constraints to arrive at the user-satisfied maps. Hence, it is tedious and labor intensive to construct polycube maps for surfaces of complicated geometry and topology. This paper aims to develop an effective method to construct polycube maps for surfaces with complicated topology and geometry. Using our method, users can simply specify how close the target polycube mimics a given shape in a quantitative way. Our algorithm can both construct a similar polycube of high geometric fidelity and compute a high-quality polycube map in an automatic fashion. In addition, our method is theoretically guaranteed to output a one-to-one map. To demonstrate the efficacy of our method, we apply the automatically-constructed polycube maps in a number of computer graphics applications, such as seamless texture tiling, T-spline construction, and quadrilateral mesh generation.     

On the All-Farthest-Segments problem for a planar set of points

In this note, we outline a very simple algorithm for the following problem: Given a set S of n points p₁,p₂,p₃,…,pn in the plane, we have O(n²) segments implicitly defined on pairs of these n points. For each point pi, find a segment from this set of implicitly defined segments that is farthest from pi. The time complexity of our algorithm is in O(nh+nlogn), where n is the number of input points, and h is the number of vertices on the convex hull of S.     

An efficient algorithm for maxdominance, with applications

Given a planar setS ofn points,maxdominance problems consist of computing, for everyp S, some function of the maxima of the subset ofS that is dominated byp. A number of geometric and graph-theoretic problems can be formulated as maxdominance problems, including the problem of computing a minimum independent dominating set in a permutation graph, the related problem of finding the shortest maximal increasing subsequence, the problem of enumerating restricted empty rectangles, and the related problem of computing the largest empty rectangle. We give an algorithm for optimally solving a class of maxdominance problems. A straightforward application of our algorithm yields improved time bounds for the above-mentioned problems. The techniques used in the algorithm are of independent interest, and include a linear-time tree computation that is likely to arise in other contexts.The research of this author was supported by the Office of Naval Research under Grants N00014-84-K-0502 and N00014-86-K-0689, and the National Science Foundation under Grant DCR-8451393, with matching funds from AT&T.This author's research was supported by the National Science Foundation under Grant DCR-8506361.     

A semidynamic construction of higher-order voronoi diagrams and its randomized analysis

Thek-Delaunay tree extends the Delaunay tree introduced in [1], and [2]. It is a hierarchical data structure that allows the semidynamic construction of the higher-order Voronoi diagrams of a finite set ofn points in any dimension. In this paper we prove that a randomized construction of thek-Delaunay tree, and thus of all the orderk Voronoi diagrams, can be done inO(n logn+k ³n) expected time and O(k²n) expected storage in the plane, which is asymptotically optimal for fixedk. Our algorithm extends tod-dimensional space with expected time complexityO(k ^(d+1)/2+1 n ^(d+1)/2) and space complexityO(k ^(d+1)/2 n ^(d+1)/2). The algorithm is simple and experimental results are given.This work has been supported in part by the ESPRIT Basic Research Action No. 3075 (ALCOM).     

A faster parameterized algorithm for set packing

We present an efficient parameterized algorithm for the (k,t)-set packing problem, in which we are looking for a collection of k disjoint sets whose union consists of t elements. The complexity of the algorithm is O(²O(t)nNlogN). For the special case of sets of bounded size, this improves the O(k(ck)n) algorithm of Jia et al. [J. Algorithms 50 (1) (2004) 106].     

A linear time algorithm for max-min length triangulation of a convex polygon

We consider the following planar max-min length triangulation problem: given a set of n points in the Euclidean plane, find a triangulation such that the length of the shortest edge in the triangulation is maximized. In this paper, a linear time algorithm is proposed for computing the max-min length triangulation of a set of points in convex position. In addition, an O(nlogn) time algorithm is proposed for computing the max-min length k-set triangulation of a set of points in convex position, where we are to compute a set of k vertices such that the max-min length triangulation on them is minimized over all possible k-set. We further show that the graph version of max-min length triangulation is NP-complete, and some common heuristics such as greedy algorithm are in general not able to give a bounded-ratio approximation to the max-min length triangulation.     

EFFICIENT PARALLEL RANGE SEARCHING AND PARTITIONING ALGORITHMS*

We present an optimal parallel construction of the range tree data structure and use this construction to solve several geometric partitioning problems. In the range tree, we show how to perform a count-mode orthogonal range query in 0(log n) time by a single processor and a report mode orthogonal range query in 0(log n) time using 0(1 + log n) processors, where k is the number of points inside the query range. We consider partitioning problems of the following nature. Given a planar point set S (∣S∣ = ri) a measure μacting on 5 and a pair of values μ1 and μ2,the task is to find a partition of S into two components S₁ and S₂ (S = S₁U S₂) such that μ(S₁) =μ1 for i=1, 2. We consider several measures like diameter under L∞ and l₁ metric; area, perimeter of the smallest enclosing axes-parallel rectangle; and the side length of the smallest enclosing axes-parallel square. All our parallel algorithms foi partitioning problems run in 0(log n) time using 0(n) processors. Our algorithms are designed for the CREW PRAM model of parallel computation.