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Fast algorithms for greedy triangulation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-50728-0_48openalex-snapshot
Greedy triangulation can be efficiently implemented in the average case
inferredcites →https://doi.org/10.1007/978-3-642-61568-9openalex-snapshot
Algorithms in Combinatorial Geometry
inferredcites →https://doi.org/10.1007/bf01840358openalex-snapshot
On approximation behavior of the greedy triangulation for convex polygons
inferredcites →https://doi.org/10.1007/bf02187695openalex-snapshot
Generalized delaunay triangulation for planar graphs
inferredcites →https://doi.org/10.1007/bfb0042804openalex-snapshot
A space efficient algorithm for the greedy triangulation
inferredcites →https://doi.org/10.1016/0020-0190(79)90104-2openalex-snapshot
Neither the greedy nor the delaunay triangulation of a planar point set approximates the optimal triangulation
inferredcites →https://doi.org/10.1016/0020-0190(87)90170-0openalex-snapshot
An ω(√n) lower bound for the nonoptimality of the greedy triangulation
inferredcites →https://doi.org/10.1016/0020-0190(89)90043-4openalex-snapshot
Voronoi diagrams with barriers and the shortest diagonal problem
inferredcites →https://doi.org/10.1016/0020-0190(89)90122-1openalex-snapshot
A space efficient greedy triangulation algorithm
inferredcites →https://doi.org/10.1016/0304-3975(89)90134-5openalex-snapshot
Heuristics for optimum binary search trees and minimum weight triangulation problems
inferredcites →https://doi.org/10.1109/sfcs.1977.21openalex-snapshot
On triangulations of a set of points in the plane
inferredcites →https://doi.org/10.1145/28395.28400openalex-snapshot
A Linear time algorithm for computing the Voronoi diagram of a convex polygon
inferredcites →https://doi.org/10.1145/41958.41981openalex-snapshot
Constrained Delaunay triangulations
inferredcites →https://doi.org/10.1145/41958.41982openalex-snapshot
An optimal algorithm for constructing the Delaunay triangulation of a set of line segments
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/https://dx.doi.org/10.6028/nist.ir.7078openalex-snapshot
TIN Techniques for Data Analysis and Surface Construction
inferred← citeshttps://doi.org/10.1007/3-540-61422-2_140openalex-snapshot
A fast heuristic for approximating the minimum weight triangulation
inferred← citeshttps://doi.org/10.1007/978-3-540-25944-2_16openalex-snapshot
Using Constraints in Delaunay and Greedy Triangulation for Contour Lines Improvement
inferred← citeshttps://doi.org/10.1007/978-3-540-78773-0_12openalex-snapshot
Optimal Higher Order Delaunay Triangulations of Polygons
inferred← citeshttps://doi.org/10.1007/bf01989747openalex-snapshot
Efficiently updating constrained Delaunay triangulations
inferred← citeshttps://doi.org/10.1007/pl00009216openalex-snapshot
A Linear-Time Approximation Scheme for Minimum Weight Triangulation of Convex Polygons
inferred← citeshttps://doi.org/10.1016/b978-0-08-102993-0.00002-3openalex-snapshot
Software algorithm and route planning
inferred← citeshttps://doi.org/10.1016/j.cageo.2008.12.017openalex-snapshot
Eliminating contour line artefacts by using constrained edges
inferred← citeshttps://doi.org/10.1016/j.comgeo.2008.02.006openalex-snapshot
Optimal higher order Delaunay triangulations of polygons
inferred← citeshttps://doi.org/10.1016/s0925-7721(97)89149-3openalex-snapshot
Fast greedy triangulation algorithms
inferred← citeshttps://doi.org/10.1145/160985.161008openalex-snapshot
A linear-time randomized algorithm for the bounded Voronoi diagram of a simple polygon
inferred← citeshttps://doi.org/10.1145/177424.177649openalex-snapshot
Fast greedy triangulation algorithms
inferred← citeshttps://doi.org/10.1145/220279.220303openalex-snapshot
Triangulations intersect nicely
inferred← citeshttps://doi.org/10.1145/220279.220305openalex-snapshot
New algorithms and empirical findings on minimum weight triangulation heuristics (extended abstract)
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