Computational geometry: an introduction
Computational geometry: an introduction
Applications of random sampling in computational geometry, II
Discrete & Computational Geometry - Selected papers from the fourth ACM symposium on computational geometry, Univ. of Illinois, Urbana-Champaign, June 6 8, 1988
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
Communications of the ACM
Asymptotically efficient in-place merging
Theoretical Computer Science
Introduction to Algorithms
In-Place Planar Convex Hull Algorithms
LATIN '02 Proceedings of the 5th Latin American Symposium on Theoretical Informatics
Divide-and-conquer in multidimensional space
STOC '76 Proceedings of the eighth annual ACM symposium on Theory of computing
Towards in-place geometric algorithms and data structures
SCG '04 Proceedings of the twentieth annual symposium on Computational geometry
Journal of Computer and System Sciences
In-place 2-d nearest neighbor search
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Constant-Working-Space Algorithms for Image Processing
Emerging Trends in Visual Computing
Optimal in-place algorithms for 3-D convex hulls and 2-D segment intersection
Proceedings of the twenty-fifth annual symposium on Computational geometry
Optimal in-place and cache-oblivious algorithms for 3-d convex hulls and 2-d segment intersection
Computational Geometry: Theory and Applications
Adaptive algorithms for planar convex hull problems
FAW'10 Proceedings of the 4th international conference on Frontiers in algorithmics
In-Place algorithms for computing (layers of) maxima
SWAT'06 Proceedings of the 10th Scandinavian conference on Algorithm Theory
In-place randomized slope selection
CIAC'06 Proceedings of the 6th Italian conference on Algorithms and Complexity
An in-place min-max priority search tree
Computational Geometry: Theory and Applications
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We develop a number of space-efficient tools including an approach to simulate divide-and-conquer space-efficiently, stably selecting and unselecting a subset from a sorted set, and computing the kth smallest element in one dimension from a multi-dimensional set that is sorted in another dimension. We then apply these tools to solve several geometric problems that have solutions using some form of divide-and-conquer. Specifically, we present a deterministic algorithm running in O(nlogn) time using O(1) extra memory given inputs of size n for the closest pair problem and a randomized solution running in O(nlogn) expected time and using O(1) extra space for the bichromatic closest pair problem. For the orthogonal line segment intersection problem, we solve the problem in O(nlogn+k) time using O(1) extra space where n is the number of horizontal and vertical line segments and k is the number of intersections.