17:
348:, the graph formed by removing the longest edge from every triangle in the Delaunay triangulation, was originally proposed as a fast method to compute the relative neighborhood graph. Although the Urquhart graph sometimes differs from the relative neighborhood graph it can be used as an approximation to the relative neighborhood graph.
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Katajainen, Jyrki; Nevalainen, Olli; Teuhola, Jukka (1987), "A linear expected-time algorithm for computing planar relative neighbourhood graphs",
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Because it is defined only in terms of the distances between points, the relative neighborhood graph can be defined for point sets in any
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and for non-Euclidean metrics. Computing the relative neighborhood graph, for higher-dimensional point sets, can be done in time
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in 1980 as a way of defining a structure from a set of points that would match human perceptions of the shape of the set.
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Jaromczyk, J. W.; Kowaluk, M. (1991), "Constructing the relative neighborhood graph in 3-dimensional
Euclidean space",
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Lingas, A. (1994), "A linear-time construction of the relative neighborhood graph from the
Delaunay triangulation",
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Supowit, K. J. (1983), "The relative neighborhood graph, with an application to minimum spanning trees",
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Jaromczyk, J.W.; Toussaint, G.T. (1992), "Relative neighborhood graphs and their relatives",
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Urquhart, R. B. (1980), "Algorithms for computation of relative neighborhood graph",
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Jaromczyk, J. W.; Kowaluk, M. (1987), "A note on relative neighborhood graphs",
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773:(1980), "Comment: Algorithms for computing relative neighborhood graph",
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The relative neighborhood graph of 100 random points in a unit square.
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373:(1980), "The relative neighborhood graph of a finite planar set",
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Andrade, Diogo Vieira; de
Figueiredo, Luiz Henrique (2001),
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showed how to construct the relative neighborhood graph of
806:"Good approximations for the relative neighbourhood graph"
605:(1982), "Computing the relative neighborhood graph in the
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Proc. 13th
Canadian Conference on Computational Geometry
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is a subgraph of it, from which it follows that it is a
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than they are to each other. This graph was proposed by
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by an edge whenever there does not exist a third point
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253:. The relative neighborhood graph can be computed in
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317:The relative neighborhood graph is an example of a
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689:(1985), "Relative neighborhood graphs in the
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588:Proc. 3rd ACM–SIAM Symp. Discrete Algorithms
494:, New York, NY, USA: ACM, pp. 233–241,
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175:points in the plane efficiently in
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36:defined on a set of points in the
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30:relative neighborhood graph (RNG
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461:Information Processing Letters
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547:Discrete Applied Mathematics
530:10.1016/0925-7721(94)90018-3
474:10.1016/0020-0190(87)90225-0
387:10.1016/0031-3203(80)90066-7
213:time. It can be computed in
7:
652:{\displaystyle L_{\infty }}
245:, for random set of points
10:
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206:{\displaystyle O(n\log n)}
40:by connecting two points
302:{\displaystyle O(n^{2})}
402:Proceedings of the IEEE
100:that is closer to both
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516:Computational Geometry
331:Delaunay triangulation
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259:Delaunay triangulation
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26:computational geometry
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790:. Reply by Urquhart,
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709:{\displaystyle L_{1}}
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625:{\displaystyle L_{1}}
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247:distributed uniformly
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235:{\displaystyle O(n)}
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775:Electronics Letters
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745:Electronics Letters
718:Pattern Recognition
661:Pattern Recognition
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444:10.1145/2402.322386
375:Pattern Recognition
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576:Agarwal, Pankaj K.
430:Journal of the ACM
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261:of the point set.
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142:Godfried Toussaint
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168:{\displaystyle n}
133:{\displaystyle q}
113:{\displaystyle p}
93:{\displaystyle r}
73:{\displaystyle q}
53:{\displaystyle p}
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339:connected graph
333:. In turn, the
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265:Generalizations
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38:Euclidean plane
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580:Mataušek, Jiří
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554:(2): 181–191,
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523:(4): 199–208,
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313:Related graphs
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781:(22): 860,
255:linear time
251:unit square
716:-metric",
687:Lee, D. T.
659:metrics",
352:References
325:. It is a
271:dimension,
148:Algorithms
645:∞
257:from the
195:
827:Category
582:(1992),
327:subgraph
32:) is an
329:of the
321:-based
249:in the
28:, the
809:(PDF)
632:and
344:The
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783:doi
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