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Proceedings ArticleDOI

Applications of random sampling in computational geometry, II

Kenneth L. Clarkson
- Vol. 4, Iss: 5, pp 1-11
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TLDR
Asymptotically tight bounds for a combinatorial quantity of interest in discrete and computational geometry, related to halfspace partitions of point sets, are given.
Abstract
Random sampling is used for several new geometric algorithms. The algorithms are “Las Vegas,” and their expected bounds are with respect to the random behavior of the algorithms. One algorithm reports all the intersecting pairs of a set of line segments in the plane, and requires O(A + n log n) expected time, where A is the size of the answer, the number of intersecting pairs reported. The algorithm requires O(n) space in the worst case. Another algorithm computes the convex hull of a point set in E3 in O(n log A) expected time, where n is the number of points and A is the number of points on the surface of the hull. A simple Las Vegas algorithm triangulates simple polygons in O(n log log n) expected time. Algorithms for half-space range reporting are also given. In addition, this paper gives asymptotically tight bounds for a combinatorial quantity of interest in discrete and computational geometry, related to halfspace partitions of point sets.

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Citations
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The quickhull algorithm for convex hulls

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Voronoi diagrams—a survey of a fundamental geometric data structure

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Jiri Matousek
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TetGen, a Delaunay-Based Quality Tetrahedral Mesh Generator

TL;DR: The essential algorithms and techniques used to develop TetGen are presented, including an efficient tetrahedral mesh data structure, a set of enhanced local mesh operations, and filtered exact geometric predicates, which can robustly handle arbitrary complex 3D geometries and is fast in practice.
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Delaunay refinement algorithms for triangular mesh generation

TL;DR: An intuitive framework for analyzing Delaunay refinement algorithms is presented that unifies the pioneering mesh generation algorithms of L. Paul Chew and Jim Ruppert, improves the algorithms in several minor ways, and helps to solve the difficult problem of meshing nonmanifold domains with small angles.
References
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Computational geometry. an introduction

TL;DR: This book offers a coherent treatment, at the graduate textbook level, of the field that has come to be known in the last decade or so as computational geometry.
Book

Computational Geometry: An Introduction

TL;DR: In this article, the authors present a coherent treatment of computational geometry in the plane, at the graduate textbook level, and point out the way to the solution of the more challenging problems in dimensions higher than two.
Book

Algorithms in Combinatorial Geometry

TL;DR: This book offers a modern approach to computational geo- metry, an area thatstudies the computational complexity of geometric problems with an important role in this study.
Journal ArticleDOI

On the shape of a set of points in the plane

TL;DR: A generalization of the convex hull of a finite set of points in the plane leads to a family of straight-line graphs, "alpha -shapes," which seem to capture the intuitive notions of "fine shape" and "crude shape" of point sets.
Journal ArticleDOI

Primitives for the manipulation of general subdivisions and the computation of Voronoi

TL;DR: The following problem is discussed: given n points in the plane (the sites) and an arbitrary query point q, find the site that is closest to q, which can be solved by constructing the Voronoi diagram of the griven sites and then locating the query point in one of its regions.