Attributed relational graph matching based on the nested assignment structure

Pattern Recognition

Volumn 43, Issue 3, 2010, Pages 914-928

  Kim, Duck Hoon ^a   Yun, Il Dong ^b   Lee, Sang Uk ^c  

^a SAMSUNG Electronics   (South Korea)

^b Hankuk University of Foreign Studies   (South Korea)

^c Seoul National University   (South Korea)

Author keywords

ARG matching; Assignment; Attributed relational graph (ARG); Nested assignment structure; Relation vector space

Indexed keywords

ASSIGNMENT ALGORITHMS; ATTRIBUTED RELATIONAL GRAPH; ATTRIBUTED RELATIONAL GRAPH MATCHING; BINARY RELATION; DISTANCE MATRICES; MATCHING PERFORMANCE; MATCHING SCHEME; TARGET OBJECT; VECTOR SPACES;

COMBINATORIAL MATHEMATICS;

PATTERN MATCHING;

EID: 70449715133     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2009.09.012     Document Type: Article

References (41)

1. Mehlhorn K., and Näher S. LEDA: A Platform for Combinatorial and Geometric Computing (1999), Cambridge University Press, Cambridge
2. Park B.G., Lee K.M., Lee S.U., and Lee J.H. Recognition of partially occluded objects using probabilistic ARG (attributed relational graph)-based matching. Computer Vision and Image Understanding 90 3 (2003) 217-241
3. Gold S., and Rangarajan A. A graduated assignment algorithm for graph matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 18 4 (1996) 377-388
4. Messmer B.T., and Bunke H. A new algorithm for error-tolerant subgraph isomorphism detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 20 5 (1998) 493-504
5. M. Pelillo, A unifying framework for relational structure matching, in: Proceedings of International Conference on Pattern Recognition, January 1998, pp. 1316-1319.
6. Ullman J.R. An algorithm for subgraph isomorphism. Journal of the ACM 23 1 (1976) 31-42
7. N.J. Nilsson, Principles of Artificial Intelligence, Tioga, Palo Alto, 1980.
8. Pelillo M., Siddiqi K., and Zucker S. Matching hierarchical structures using association graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence 21 11 (1999) 1105-1120
9. Tsai W.H., and Fu K.S. Error-correcting isomorphisms of attributed relational graphs for pattern recognition. IEEE Transactions on Systems, Man, and Cybernetics 9 (1979) 757-768
10. Tsai W.H., and Fu K.S. Subgraph error-correcting isomorphisms for syntactic pattern recognition. IEEE Transactions on Systems, Man, and Cybernetics 13 1 (1983) 48-62
11. Rosenfeld A., Hummel R., and Zucker S. Scene labeling by relaxation operations. IEEE Transactions on Systems, Man, and Cybernetics 6 6 (1976) 420-433
12. Faugeras O.D., and Price K.E. Semantic description of aerial images using stochastic labeling. IEEE Transactions on Pattern Analysis and Machine Intelligence 3 6 (1981) 633-642
13. Li S.Z. Matching: invariant to translations, rotations and scale changes. Pattern Recognition 25 6 (1992) 583-594
14. Christmas W.J., Kittler J., and Petrou M. Structural matching in computer vision using probabilistic relaxation. IEEE Transactions on Pattern Analysis and Machine Intelligence 17 8 (1995) 749-764
15. Kittler J., Petrou M., and Christmas W.J. A non-iterative probabilistic method for contextual correspondence matching. Pattern Recognition 31 10 (1998) 1455-1468
16. Luo B., and Hancock E.R. Structural graph matching using the EM algorithm and singular value decomposition. IEEE Transactions on Pattern Analysis and Machine Intelligence 23 10 (2001) 1120-1136
17. Lozano M.A., and Escolano F. Protein classification by matching and clustering surface graphs. Pattern Recognition 39 4 (2006) 539-551
18. van Wyk B.J., and van Wyk M.A. A POCS-based graph matching algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence 26 11 (2004) 1526-1530
19. Umeyama S. An eigendecomposition approach to weighted graph matching problems. IEEE Transactions on Pattern Analysis and Machine Intelligence 10 5 (1988) 695-703
20. Xu L., and King I. A PCA approach for fast retrieval of structural patterns in attributed graphs. IEEE Transactions on Systems Man and Cybernetics-Part B: Cybernetics 31 5 (2001) 812-817
21. Almohamad H.A., and Duffuaa S.O. A linear programming approach for the weighted graph matching problem. IEEE Transactions on Pattern Analysis and Machine Intelligence 15 5 (1993) 522-525
22. Huet B., and Hancock E.R. Relational object recognition from large structural libraries. Pattern Recognition 35 9 (2002) 1895-1915
23. Duda R.O., Hart P.E., and Stork D.G. Pattern Classification (2000), Wiley-Interscience, New York
24. Vaidya P.M. An O (n log n) algorithm for the all-nearest-neighbors problem. Discrete & Computational Geometry 4 2 (1989) 101-115
25. Huttenlocher D.P., Klanderman G.A., and Rucklidge W.J. Comparing images using the Hausdorff distance. IEEE Transactions on Pattern Analysis and Machine Intelligence 15 9 (1993) 850-863
26. Rucklidge W. Efficiently locating objects using the Hausdorff distance. International Journal of Computer Vision 24 3 (1997) 251-270
27. Cherkassky B.V., Goldberg A.V., Martin P., Setubal J.C., and Stolfi J. Augment or push? A computational study of bipartite matching and unit-capacity flow algorithms. Journal of Experimental Algorithmics 3 8 (1998)
28. 5 / 2 algorithm for maximum matchings in bipartite graphs. SIAM Journal of Computing 2 (1973) 225-231
29. Kuhn H.W. The Hungarian method for the assignment problem. Naval Research Logistics Quarterly 2 (1955) 83-97
30. A. Shokoufandeh, S. Dickinson, Applications of bipartite matching to problems in object recognition, in: Proceedings of ICCV Workshop on Graph Algorithms and Computer Vision, September 1999.
31. Ahuja R.K., Magnanti T.L., and Orlin J.B. Network Flows: Theory, Algorithms, and Applications (1993), Prentice-Hall, Englewood Cliffs, NJ
32. Rubner Y., Tomasi C., and Guibas L.J. The earth mover's distance as a metric for image retrieval. International Journal of Computer Vision 40 2 (2000) 99-121
33. Hitchcock F.L. The distribution of a product from several sources to numerous localities. Journal of Mathematics and Physics 20 (1941) 224-230
34. 〈http://sourceforge.net/projects/opencvlibrary/〉.
35. D.H. Kim, I.D. Yun, S.U. Lee, A new attributed relational graph matching algorithm using the nested structure of earth mover's distance, in: Proceedings of International Conference on Pattern Recognition, vol. 1, August 2004, pp. 48-51.
36. Dempster A., Laird N., and Rubin D. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society-Series B 39 1 (1977) 1-38
37. S. Cohen, L.J. Guibas, The earth mover's distance under transformation sets, in: Proceedings of International Conference on Computer Vision, vol. 2, September 1999, pp. 1076-1083.
38. Qiu H., and Hancock E.R. Graph matching and clustering using spectral partitions. Pattern Recognition 39 1 (2006) 22-34
39. van Wyk B.J., and van Wyk M.A. Kronecker product graph matching. Pattern Recognition 36 2 (2003) 2019-2030
40. K. Grauman, T. Darrell, Efficient image matching with distributions of local invariant features, in: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, June 2005, pp. 627-634.
41. H. Ling, K. Okada, EMD-L1: an efficient and robust algorithm for comparing histogram-based descriptors, in: Proceedings of European Conference on Computer Vision, vol. 3, May 2006, pp. 330-343.