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Relative neighborhood graph

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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. 657: 211: 307: 714: 630: 240: 173: 138: 118: 98: 78: 58: 458:
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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The relative neighborhood graph of 100 random points in a unit square.
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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
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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
695: 638: 611: 279: 253:. The relative neighborhood graph can be computed in 219: 181: 161: 126: 106: 86: 66: 46: 803: 317:The relative neighborhood graph is an example of a 708: 651: 624: 584:"Relative neighborhood graphs in three dimensions" 399: 301: 234: 205: 167: 132: 112: 92: 72: 52: 824: 543: 489: 574: 689:(1985), "Relative neighborhood graphs in the 601: 588:Proc. 3rd ACM–SIAM Symp. Discrete Algorithms 494:, New York, NY, USA: ACM, pp. 233–241, 769: 559: 528: 442: 369: 742: 15: 426: 152: 825: 512: 492:Proc. 3rd Symp. Computational Geometry 485: 483: 365: 363: 361: 685: 480: 175:points in the plane efficiently in 13: 644: 358: 264: 36:defined on a set of points in the 14: 844: 312: 30:relative neighborhood graph (RNG 797: 763: 736: 679: 335:Euclidean minimum spanning tree 595: 568: 537: 506: 461:Information Processing Letters 451: 420: 393: 296: 283: 229: 223: 200: 185: 1: 351: 147: 730:10.1016/0031-3203(85)90023-8 673:10.1016/0031-3203(82)90070-X 561:10.1016/0166-218X(91)90069-9 547: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: 849: 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 710: 653: 626: 516:Computational Geometry 331:Delaunay triangulation 303: 259:Delaunay triangulation 236: 207: 169: 134: 114: 94: 74: 54: 26:computational geometry 21: 790:. Reply by Urquhart, 711: 709:{\displaystyle L_{1}} 654: 627: 625:{\displaystyle L_{1}} 304: 247:distributed uniformly 237: 208: 170: 135: 115: 95: 75: 55: 19: 693: 636: 609: 277: 235:{\displaystyle O(n)} 217: 179: 159: 124: 104: 84: 64: 44: 787:10.1049/el:19800611 775:Electronics Letters 757:10.1049/el:19800386 745:Electronics Letters 718:Pattern Recognition 661:Pattern Recognition 500:10.1145/41958.41983 444:10.1145/2402.322386 375:Pattern Recognition 706: 649: 622: 576:Agarwal, Pankaj K. 430:Journal of the ACM 299: 261:of the point set. 232: 203: 165: 142:Godfried Toussaint 130: 110: 90: 70: 50: 22: 168:{\displaystyle n} 133:{\displaystyle q} 113:{\displaystyle p} 93:{\displaystyle r} 73:{\displaystyle q} 53:{\displaystyle p} 840: 833:Geometric graphs 817: 815: 810: 801: 795: 789: 771:Toussaint, G. T. 767: 761: 759: 740: 734: 732: 715: 713: 712: 707: 705: 704: 683: 677: 675: 658: 656: 655: 650: 648: 647: 631: 629: 628: 623: 621: 620: 599: 593: 591: 590:, pp. 58–65 572: 566: 564: 563: 541: 535: 533: 532: 510: 504: 502: 487: 478: 476: 455: 449: 447: 446: 424: 418: 416: 414:10.1109/5.163414 408:(9): 1502–1517, 397: 391: 389: 371:Toussaint, G. T. 367: 308: 306: 305: 300: 295: 294: 272: 241: 239: 238: 233: 212: 210: 209: 204: 174: 172: 171: 166: 139: 137: 136: 131: 119: 117: 116: 111: 99: 97: 96: 91: 79: 77: 76: 71: 59: 57: 56: 51: 34:undirected graph 848: 847: 843: 842: 841: 839: 838: 837: 823: 822: 821: 820: 808: 802: 798: 768: 764: 751:(14): 556–557, 741: 737: 700: 696: 694: 691: 690: 684: 680: 643: 639: 637: 634: 633: 616: 612: 610: 607: 606: 600: 596: 573: 569: 542: 538: 511: 507: 488: 481: 456: 452: 425: 421: 398: 394: 368: 359: 354: 339:connected graph 333:. In turn, the 315: 290: 286: 278: 275: 274: 270: 267: 265:Generalizations 218: 215: 214: 180: 177: 176: 160: 157: 156: 150: 125: 122: 121: 105: 102: 101: 85: 82: 81: 65: 62: 61: 45: 42: 41: 38:Euclidean plane 12: 11: 5: 846: 836: 835: 819: 818: 796: 762: 735: 724:(5): 327–332, 703: 699: 678: 667:(3): 189–192, 646: 642: 619: 615: 594: 580:Mataušek, Jiří 567: 554:(2): 181–191, 536: 523:(4): 199–208, 505: 479: 450: 437:(3): 428–448, 419: 392: 381:(4): 261–268, 356: 355: 353: 350: 346:Urquhart graph 314: 313:Related graphs 311: 298: 293: 289: 285: 282: 266: 263: 231: 228: 225: 222: 202: 199: 196: 193: 190: 187: 184: 164: 153:Supowit (1983) 149: 146: 129: 109: 89: 69: 49: 9: 6: 4: 3: 2: 845: 834: 831: 830: 828: 814: 807: 800: 793: 788: 784: 780: 776: 772: 766: 758: 754: 750: 746: 739: 731: 727: 723: 719: 701: 697: 688: 682: 674: 670: 666: 662: 640: 617: 613: 604: 598: 589: 585: 581: 577: 571: 562: 557: 553: 549: 548: 540: 531: 526: 522: 518: 517: 509: 501: 497: 493: 486: 484: 475: 471: 467: 463: 462: 454: 445: 440: 436: 432: 431: 423: 415: 411: 407: 403: 396: 388: 384: 380: 376: 372: 366: 364: 362: 357: 349: 347: 342: 340: 336: 332: 328: 324: 323:beta skeleton 320: 310: 291: 287: 280: 262: 260: 256: 252: 248: 244: 243:expected time 226: 220: 197: 194: 191: 188: 182: 162: 154: 145: 143: 127: 107: 87: 67: 47: 39: 35: 31: 27: 18: 812: 799: 778: 774: 765: 748: 744: 738: 721: 717: 681: 664: 660: 603:O'Rourke, J. 597: 587: 570: 551: 545: 539: 520: 514: 508: 491: 468:(2): 77–86, 465: 459: 453: 434: 428: 422: 405: 401: 395: 378: 374: 343: 316: 268: 151: 29: 23: 792:pp. 860–861 781:(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 319:lens 120:and 60:and 783:doi 753:doi 726:doi 669:doi 556:doi 525:doi 496:doi 470:doi 439:doi 410:doi 383:doi 192:log 24:In 829:: 811:, 779:16 777:, 749:16 747:, 722:18 720:, 665:15 663:, 586:, 578:; 552:31 550:, 519:, 482:^ 466:25 464:, 435:30 433:, 406:80 404:, 379:12 377:, 360:^ 341:. 309:. 816:. 794:. 785:: 760:. 755:: 733:. 728:: 702:1 698:L 676:. 671:: 641:L 618:1 614:L 592:. 565:. 558:: 534:. 527:: 521:4 503:. 498:: 477:. 472:: 448:. 441:: 417:. 412:: 390:. 385:: 297:) 292:2 288:n 284:( 281:O 230:) 227:n 224:( 221:O 201:) 198:n 189:n 186:( 183:O 163:n 128:q 108:p 88:r 68:q 48:p

Index


computational geometry
undirected graph
Euclidean plane
Godfried Toussaint
Supowit (1983)
expected time
distributed uniformly
unit square
linear time
Delaunay triangulation
lens
beta skeleton
subgraph
Delaunay triangulation
Euclidean minimum spanning tree
connected graph
Urquhart graph



Toussaint, G. T.
doi
10.1016/0031-3203(80)90066-7
doi
10.1109/5.163414
Journal of the ACM
doi
10.1145/2402.322386
Information Processing Letters

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