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相关论文: Degree of Convexity and Expected Distances in Poly…

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Let $S$ be a subset of $\mathbb{R}^d$ with finite positive Lebesgue measure. The Beer index of convexity $\operatorname{b}(S)$ of $S$ is the probability that two points of $S$ chosen uniformly independently at random see each other in $S$.…

度量几何 · 数学 2016-12-30 Martin Balko , Vít Jelínek , Pavel Valtr , Bartosz Walczak

Given a simple polygon $P$ consisting of $n$ vertices, we study the problem of designing space-efficient algorithms for computing (i) the visibility polygon of a point inside $P$, (ii) the weak visibility polygon of a line segment inside…

计算几何 · 计算机科学 2012-04-13 Minati De , Anil Maheshwari , Subhas C. Nandy

Our interest is in paths between pairs of vertices that go through at least one of a subset of the vertices known as beer vertices. Such a path is called a beer path, and the beer distance between two vertices is the length of the shortest…

数据结构与算法 · 计算机科学 2022-09-30 Rathish Das , Meng He , Eitan Kondratovsky , J. Ian Munro , Anurag Murty Naredla , Kaiyu Wu

Consider a metric space $(P,dist)$ with $N$ points whose doubling dimension is a constant. We present a simple, randomized, and recursive algorithm that computes, in $O(N \log N)$ expected time, the closest-pair distance in $P$. To generate…

计算几何 · 计算机科学 2021-02-03 Anil Maheshwari , Wolfgang Mulzer , Michiel Smid

In this paper, we study the following problem of reconstructing a simple polygon: Given a cyclically ordered vertex sequence of an unknown simple polygon P of n vertices and, for each vertex v of P, the sequence of angles defined by all the…

计算几何 · 计算机科学 2010-09-15 Danny Z. Chen , Haitao Wang

This paper describes novel and fast, simple and robust algorithm with O(N) expected complexity which enables to decrease run-time needed to find an exact maximum distance of two points in E2. The proposed algorithm has been evaluated…

计算几何 · 计算机科学 2022-08-23 Vaclav Skala

We show how to compute for $n$-vertex planar graphs in $O(n^{11/6}{\rm polylog}(n))$ expected time the diameter and the sum of the pairwise distances. The algorithms work for directed graphs with real weights and no negative cycles. In…

数据结构与算法 · 计算机科学 2018-05-14 Sergio Cabello

In this paper, we derive formulas for the analytical calculation of the moments of the distance between two uniformly and independently distributed random points in an $n$-sided regular polygon. A number of closed form expressions is…

概率论 · 数学 2021-01-12 Uwe Bäsel

Let $S$ be a set of $n$ points in the plane. We present several different algorithms for finding a pair of points in $S$ such that any disk that contains that pair must contain at least $cn$ points of $S$, for some constant $c>0$. The first…

计算几何 · 计算机科学 2026-01-29 Prosenjit Bose , Guillermo Esteban , Tyler Tuttle

We present several algorithms for computing the visibility polygon of a simple polygon $P$ from a viewpoint inside the polygon, when the polygon resides in read-only memory and only few working variables can be used. The first algorithm…

计算几何 · 计算机科学 2013-04-09 Luis Barba , Matias Korman , Stefan Langerman , Rodrigo I. Silveira

In [3], algorithms to compute the density of the distance to a random variable uniformly distributed in (a) a ball, (b) a disk, (c) a line segment, or (d) a polygone were introduced. For case (d), the algorithm, based on Green's theorem,…

计算几何 · 计算机科学 2019-06-06 Vincent Guigues

We consider the following geometric optimization problem: find a convex polygon of maximum area contained in a given simple polygon $P$ with $n$ vertices. We give a randomized near-linear-time $(1-\varepsilon)$-approximation algorithm for…

计算几何 · 计算机科学 2017-10-17 Sergio Cabello , Josef Cibulka , Jan Kynčl , Maria Saumell , Pavel Valtr

Given two points in a simple polygon $P$ of $n$ vertices, its geodesic distance is the length of the shortest path that connects them among all paths that stay within $P$. The geodesic center of $P$ is the unique point in $P$ that minimizes…

计算几何 · 计算机科学 2015-01-06 Hee-Kap Ahn , Luis Barba , Prosenjit Bose , Jean-Lou de Carufel , Matias Korman , Eunjin Oh

We propose a self-improving algorithm for computing Voronoi diagrams under a given convex distance function with constant description complexity. The $n$ input points are drawn from a hidden mixture of product distributions; we are only…

计算几何 · 计算机科学 2021-10-26 Siu-Wing Cheng , Man Ting Wong

Coudert et al. (SODA'18) proved that under the Strong Exponential-Time Hypothesis, for any $\epsilon >0$, there is no ${\cal O}(2^{o(k)}n^{2-\epsilon})$-time algorithm for computing the diameter within the $n$-vertex cubic graphs of…

数据结构与算法 · 计算机科学 2020-11-18 Guillaume Ducoffe

Consider a set $P$ of $n$ points picked uniformly and independently from $[0,1]^d$ for a constant dimension $d$ -- such a point set is extremely well behaved in many aspects. For example, for a fixed $r \in [0,1]$, we prove a new…

计算几何 · 计算机科学 2023-11-01 Sariel Har-Peled , Elfarouk Harb

Let P be a set of points in R^d, and let M be a function that maps any subset of P to a positive real number. We examine the problem of computing the exact mean and variance of M when a subset of points in P is selected according to a…

数据结构与算法 · 计算机科学 2016-10-13 Frank Staals , Constantinos Tsirogiannis

We introduce the \emph{visibility center} of a set of points inside a polygon -- a point $c_V$ such that the maximum geodesic distance from $c_V$ to see any point in the set is minimized. For a simple polygon of $n$ vertices and a set of…

计算几何 · 计算机科学 2022-12-06 Anna Lubiw , Anurag Murty Naredla

In this paper we present several results on the expected complexity of a convex hull of $n$ points chosen uniformly and independently from a convex shape. (i) We show that the expected number of vertices of the convex hull of $n$ points,…

计算几何 · 计算机科学 2011-11-24 Sariel Har-Peled

We present an algorithm that computes the girth of the intersection graph of $n$ given line segments in the plane in $O(n^{1.483})$ expected time. This is the first such algorithm with $O(n^{3/2-\varepsilon})$ running time for a positive…

计算几何 · 计算机科学 2026-03-24 Timothy M. Chan , Yuancheng Yu
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