computational geometry


Also found in: Acronyms, Wikipedia.

computational geometry

(mathematics)
The study of algorithms for combinatorial, topological, and metric problems concerning sets of points, typically in Euclidean space. Representative areas of research include geometric search, convexity, proximity, intersection, and linear programming.
Mentioned in ?
References in periodicals archive ?
16th Canadian Conference on Computational Geometry, Montreal, Quebec, Canada, 2004, pp.
Caption: Martin Demaine (left) and his son Erik have drawn on mathematics and computational geometry to design fonts that incorporate puzzles.
O'Rourke, Discrete and Computational Geometry, Princeton University Press, Princeton, New Jersey, 2011.
The algorithm starts by generating the convex hull of a set of points using one of the known and robust computational geometry algorithms.
Detecting undersampling in surface reconstruction, in Proceedings of the Seventeenth Annual Symposium on Computational Geometry (Medford, Massachusetts, United States).
Although the algorithmic study of convex hulls is as old as computational geometry itself, the basic problem of optimally maintaining the planar convex hull under insertions and deletions of points [Mehlhorn 1984; Preparata and Shamos 1985] remains unsolved and has been regarded by some as one of the foremost open problems in the area [Chiang and Tamassia 1992; Hershberger and Suri 1996].
The Division provides expertise in a wide variety of areas, such as nonlinear dynamics, stochastic methods, optimization, partial differential equations (PDE), computational geometry, inverse problems, linear algebra, and numerical analysis.
The technique was originally motivated by so-called parametric-optimization problems in combinatorial optimization, and did not receive much attention by the computational geometry community until the late 1980s.
SCG 98: 14TH ACM SYMPOSIUM ON COMPUTATIONAL GEOMETRY Minneapolis, MN.
Objective: The TITANIUM proposal aims to develop a software demonstrator for geometry processing and 3D urban modeling, in order to facilitate the pre-commercialization of novel software components for the Computational Geometry Algorithms Library.
Then they survey various areas in which probabilistic techniques have been successful, among them discrepancy and random graphs, theoretical computer science, circuit complexity, computational geometry, and de-randomizing randomized algorithms.
The design of “Glittering Machines” is informed by bioluminescent fauna, crystal morphology and computational geometry.

Full browser ?