13.3 Graph Matching and Relaxation

Chapter Contents (Back)
Object Recognition. Matching, Graphs. Graph Matching.

13.3.1 Graph Matching Theoretical Issues

Chapter Contents (Back)
Constraint Satisfaction. Matching, Graphs. Graph Matching, Theory. Generally these papers restrict the problem to an exact matching problem, which is the easy case. Also discrete relaxation: See also Discrete Relaxation Theoretical Issues. See also Social Networks, Creation, Visualization, Use.

Corneil, D.G., and Gotlieb, C.C.,
An Efficient Algorithm for Graph Isomorphism,
JACM(17), No. 1, January 1970, pp. 51-64. Graph Isomorphism. This technique for isomorphism derived two graphs from the input graphs. The original graphs are isomorphic only if the derived graphs are identical. The algorithm, complexity O(N^n ) is more efficient than the early renumbering techniques that were O(N!), because the power is usually no more than 5 (for some special cases, usually it is lower). This technique applies to non-directed graphs and was not extended to bi-directional graphs, except as a part of an O(N!) algorithm. BibRef 7001

Corneil, D.G., and Kirkpatrick, D.G.,
A Theoretical Analysis of Various Heuristics for the Graph Isomorphism Problem,
SIAM_JC(9), 1980, pp. 281-297. BibRef 8000

Shaw, A.C.,
Parsing of Graph-Representable Pictures,
JACM(17), No. 3, July 1970, pp. 453-481. BibRef 7007

Shaw, A.C.[Alan C.],
A Formal Picture Description Scheme as a Basis for Picture Processing Systems,
InfoControl(14), No. 1, January 1969, pp. 9-52. BibRef 6901

Mallgren, W.R., Shaw, A.C.,
Graphical transformations and hierarchic picture structures,
CGIP(8), No. 2, October 1978, pp. 237-258.
WWW Link. 0501
BibRef

Hopcroft, J.E., and Tarjan, R.E.,
Isomorphism of Planar Graphs,
CCComp(131-152). 1972. BibRef 7200

Tarjan, R.E.,
Depth First Search and Linear Graph Algorithms,
SIAM_JC(1), No. 1, 1972, pp 146-160. BibRef 7200

Pfaltz, J.L.,
Graph Structures,
JACM(19), No. 3, July 1972, pp. 411-422. BibRef 7207

Berztiss, A.T.,
A Backtrack Procedure for Isomorphism of Directed Graphs,
JACM(20), No. 3, July, 1973, pp. 365-372. Graph Isomorphism. This algorithm, applied to directed graphs, first transforms the graph representation into a linear string that describes the connections between nodes. These strings start from strings describing each node and combine to form a single string describing the entire graph. From the combination rules a matching string is formed by a tree search procedure that adds one node at a time and retains only those possible strings that match the pattern. This technique proved effective for most real graphs even though it does not escape the possible worst cases. BibRef 7307

Ullmann, J.R.,
A Consistency Technique for Pattern Association,
IT(8), No. 5, September 1962, pp. 74-81. Relaxation, Discrete. Describes a simple hardware implementation, lacks an abstract mathematical formulation -- hardware is easier than software in 1962. BibRef 6209

Ullmann, J.R.,
Distributive Implementation of Relational Operations,
IEE-P(E: 137), No. 4, July 1990, pp. 283-294. Updated version of original paper. BibRef 9007

Ullmann, J.R.,
Parallel Recognition of Idealised Line Characters,
Kybernetic(2), Part 5, June 1965, pp. 221-226. Original discrete relaxation with mathematical fomulation. This paper is available:
PDF File. Also from the Springer site:
Springer DOI It has been made available with kind permission of Springer Science+Business Media, A short version of this paper is available:
PDF File. See also Algorithm for Subgraph Isomorphism, An. BibRef 6506

Ullmann, J.R.,
A Use of Continutiy in Character Recognition,
SMC(4), No. 3, May 1974, pp. 294-300. Using binary constraint propogation, can a character be a distorted image of another character. See also Recognition experiments with typed numerals from envelopes in the mail. BibRef 7405

Ullmann, J.R.,
Subset Methods for Recognising Distorted Patterns,
SMC(7), No. 3, March 1977, pp. 180-191. Non-binary constraint propogation, not all boundaries need to be closed. BibRef 7703

Ullmann, J.R.,
Pattern Recognition Using Degenerate Reference Data,
PRAI-76(508-528). Distorted patterns compared to reference patterns. Non-binary propogation. BibRef 7600

Berge, C.,
Graphs and Hypergraphs,
North HollandAmsterdam, 1973. BibRef 7300

Bron, C., and Kerbosch, J.,
Algorithm 457: Finding All Cliques in an Undirected Graph (H),
CACM(16), 1973. BibRef 7300

Osteen, R., and Tou, J.T.,
A Clique-Directed Algorithm Based on Neighborhoods in Graphs,
CIS(2), No. 4, December 1973, pp. 257-268. BibRef 7312

van Scoy, F.L.,
The Parallel Recognition of Classes of Graphs,
TC(29), 1980, pp. 563-570. BibRef 8000

Ghahraman, D.E., Wong, A.K.C., Au, T.,
Graph Optimal Monomorphism Algorithm,
SMC(10), April 1980, pp. 181-188. BibRef 8004

Ghahraman, D.E., Wong, A.K.C., Au, T.,
Graph Monomorphism Algorithms,
SMC(10), 1980, pp. 189-196. BibRef 8000

Bhat, K.V.S.,
Refined Vertex Codes and Vertex Partitioning Methodology for Graph Isomorphism Testing,
SMC(10), 1980, pp. 610-615. BibRef 8000

Forgy, C.L.,
Rete: A Fast Algorithm for the Many Pattern/Many Object Pattern Match Problem,
AI(19), No. 1, September 1982, pp. 17-37.
WWW Link. Precompute the network to make matching fast. Intended for production rule matching. BibRef 8209

Fowler, G., Haralick, R.M., Gray, F.G., Feustel, C., and Grinstead, C.,
Efficient Graph Automorphism by Vertex Partitioning,
AI(21), No. 1-2, March 1983, pp. 245-269.
Elsevier DOI BibRef 8303

Mehlhorn, K.,
Data Structure and Algorithms 2: Graphs Algorithms and NP-Completeness,
Springer-Verlag1984. BibRef 8400 Book BibRef

Quinn, M.J., Deo, N.,
Parallel Graph Algorithms,
Surveys(16), No. 3, September 1984, pp. 319-348. Survey, Graph Matching. BibRef 8409

Nyo, H.L., Suk, M.,
A Polynomial Time Algorithm for Subpattern Matching,
PIEEE(74), 1986, pp. 375-377. BibRef 8600

Galil, Z.,
Efficient Algorithms for Finding Maximum Matching in Graphs,
Surveys(18), No. 1, March 1986, pp. 23-38. See also String Matching in Real Time. BibRef 8603

Thathachar, M.A.L., and Sastry, P.S.,
Relaxation Labeling with Learning Automata,
PAMI(8), No. 2, March 1986, pp. 256-268. BibRef 8603

Davies, E.R.,
The Minimal Match Graph and its Use to Speed Identification of Maximal Cliques,
SP(22), 1991, pp. 329-343. BibRef 9100

Davies, E.R.,
Alternative to Abstract Graph Matching for Locating Objects from Their Salient Features,
IVC(9), No. 4, August 1991, pp. 252-261.
WWW Link. BibRef 9108

Simic, P.,
Constrained Nets for Graph matching and Other Quadratic Assignment Problems,
NeurComp(3), 1991, pp. 268-291. BibRef 9100

Almohamad, H.A., and Duffuaa, S.O.,
A Linear Programming Approach fo the Weighted Graph Matching Problem,
PAMI(15), No. 5, May 1993, pp. 522-525.
IEEE DOI Linear Programming. BibRef 9305

Seong, D.S., Choi, Y.K., Kim, H.S., Park, K.H.,
An Algorithm For Optimal Isomorphism Between 2 Random Graphs,
PRL(15), No. 4, April 1994, pp. 321-327. BibRef 9404

Jeavons, P.G.[Peter G.], Coope, M.C.[Martin C.],
Tractable Constraints on Ordered Domains,
AI(79), No. 2, January 1996, pp. 327-339.
WWW Link. By ordering the domain it is possible to limit the constraints to pairwise constraints, then get a linear solution. Used in See also Linear-time algorithms for testing the realisability of line drawings of curved objects. BibRef 9601

Pedrycz, W.,
Classification of Relational Patterns as a Decomposition Problem,
PRL(17), No. 1, January 10 1996, pp. 91-99. BibRef 9601

Pedrycz, W.,
Neurocomputations in relational systems,
PAMI(13), No. 3, March 1991, pp. 289-297.
IEEE DOI 0401
BibRef

Cucka, P., Netanyahu, N.S., and Rosenfeld, A.,
Learning in Navigation: Goal Finding in Graphs,
PRAI(10), 1996, pp. 429-446. BibRef 9600

Jumarie, G.,
Informational Similarity of Graphs in Syntactic Pattern Recognition,
PRL(15), 1994, pp. 1177-1181. BibRef 9400

Owolabi, O.,
A Graph Canonization Method For Pattern Recognition,
PRL(12), 1991, pp. 701-705. BibRef 9100

Seong, D.S., Kim, H.S., Park, K.H.,
Incremental Clustering of Attributed Graphs,
SMC(23), 1993, pp. 1399-1411. BibRef 9300

Goldman, R.P., Charniak, E.,
A language for construction of belief networks,
PAMI(15), No. 3, March 1993, pp. 196-208.
IEEE DOI 0401
BibRef

Buckley, M., Yang, J.,
Regularized Shortest Path Extraction,
PRL(18), No. 7, July 1997, pp. 621-629. 9711
Shortest path through a graph. BibRef

Barbehenn, M.,
A Note on the Complexity of Dijkstras Algorithm for Graphs with Weighted Vertices,
TC(47), No. 2, February 1998, pp. 263-263. 9803
BibRef

Suganthan, P.N., Yan, H., Teoh, E.K., Mital, D.P.,
Optimal Encoding of Graph Homomorphism Energy Using Fuzzy Information Aggregation Operators,
PR(31), No. 5, May 1998, pp. 623-639.
WWW Link. 9805
BibRef

Abdulrahim, M.[Mohammad], Misra, M.[Manavendra],
A Graph Isomorphism Algorithm for Object Recognition,
PAA(1), No. 3, 1998, pp. xx-yy. BibRef 9800

Bunke, H.,
Error Correcting Graph Matching: On the Influence of the Underlying Cost Function,
PAMI(21), No. 9, September 1999, pp. 917-922.
IEEE DOI For any cost function, there are an infinite number of others that lead to the same optimal error correcting matching. BibRef 9909

Miller, D.A.[Douglas A.], Zucker, S.W.[Steven W.],
Cliques, computation, and computational tractability,
PR(33), No. 4, April 2000, pp. 535-542.
WWW Link. 0002
BibRef

Luo, B., Hancock, E.R.,
Structural Graph Matching Using the EM Algorithm and Singular Value Decomposition,
PAMI(23), No. 10, October 2001, pp. 1120-1136.
IEEE DOI 0110
BibRef
Earlier:
Symbolic Graph Matching Using the EM Algorithm and Singular Value Decomposition,
ICPR00(Vol II: 141-144).
IEEE DOI 0009
See also Multiple Line-Template Matching with the EM Algorithm. See also Registering Incomplete Radar Images Using the EM Algorithm. BibRef

Luo, B., Hancock, E.R.,
A robust eigen-decomposition framework for inexact graph-matching,
CIAP01(465-470).
WWW Link. 0210
BibRef

Carcassoni, M.[Marco], Hancock, E.R.[Edwin R.],
Weighted Graph-Matching Using Modal Clusters,
CAIP01(142 ff.).
Springer DOI 0210
BibRef

Dickinson, S.J.[Sven J.], Pelillo, M.[Marcello], Zabih, R.[Ramin],
Introduction to the Special Section on Graph Algorithms and Computer Vision,
PAMI(23), No. 10, October 2001, pp. 1049-1052.
IEEE DOI 0110
BibRef

Ostergard, P.,
A Fast Algorithm for the Maximum Clique Problem,
DiscAppMath(120), 2002, pp. 197-207. BibRef 0200

Wang, J.T.L.[Jason T.L.], Zhang, K.Z.[Kai-Zhong], Chang, G.[George], Shasha, D.[Dennis],
Finding approximate patterns in undirected acyclic graphs,
PR(35), No. 2, February 2002, pp. 473-483.
WWW Link. 0201
BibRef

Raphael, C.[Christopher],
Coarse-to-Fine Dynamic Programming,
PAMI(23), No. 12, December 2001, pp. 1379-1390.
IEEE DOI 0112
Dynamic Programming. Applied to mine detection. Generalize dynamic programming to hierarchical system. BibRef

Fernandez-Madrigal, J.A.[Juan-Antonio], Gonzalez, J.[Javier],
Multihierarchical Graph Search,
PAMI(24), No. 1, January 2002, pp. 103-113.
IEEE DOI 0201
Applied to path planning. BibRef

de Santo, M., Foggia, P., Sansone, C., Vento, M.,
A large database of graphs and its use for benchmarking graph isomorphism algorithms,
PRL(24), No. 8, May 2003, pp. 1067-1079.
WWW Link. 0304
BibRef

Cordella, L.P., Sansone, C., Tortorella, F., Vento, M.[Mario], Foggia, P.,
Graph Matching: A Fast Algorithm and its Evaluation,
ICPR98(Vol II: 1582-1584).
IEEE DOI 9808
BibRef

Cordella, L.P., Foggia, P., Sansone, C., Vento, M.,
A (Sub)Graph Isomorphism Algorithm for Matching Large Graphs,
PAMI(26), No. 10, October 2004, pp. 1367-1372.
IEEE Abstract. 0409
BibRef
Earlier:
Fast Graph Matching for Detecting CAD Image Components,
ICPR00(Vol II: 1034-1037).
IEEE DOI 0009
BibRef
Earlier:
Performance evaluation of the VF graph matching algorithm,
CIAP99(1172-1177).
IEEE DOI 9909
BibRef
Earlier:
An Efficient Algorithm for the Inexact Matching of ARG Graphs Using a Contextual Transformational Model,
ICPR96(III: 180-184).
IEEE DOI 9608
(Univ. di Napoli, I) Earlier version worked on small and medium sized graphs. This works for large graphs. BibRef

Carletti, V.[Vincenzo], Foggia, P.[Pasquale], Vento, M.[Mario], Jiang, X.Y.[Xiao-Yi],
Report on the First Contest on Graph Matching Algorithms for Pattern Search in Biological Databases,
GbRPR15(178-187).
Springer DOI 1511
BibRef

Carletti, V.[Vincenzo], Foggia, P.[Pasquale], Saggese, A.[Alessia], Vento, M.[Mario],
Introducing VF3: A New Algorithm for Subgraph Isomorphism,
GbRPR17(128-139).
Springer DOI 1706
BibRef

Carletti, V.[Vincenzo], Foggia, P.[Pasquale], Vento, M.[Mario],
Performance Comparison of Five Exact Graph Matching Algorithms on Biological Databases,
PR-PS-BB13(409-417).
Springer DOI 1309
BibRef

Conte, D.[Donatello], Foggia, P.[Pasquale], Jolion, J.M.[Jean-Michel], Vento, M.[Mario],
A graph-based, multi-resolution algorithm for tracking objects in presence of occlusions,
PR(39), No. 4, April 2006, pp. 562-572.
WWW Link. 0604
Object tracking; Occlusion problem; Graph pyramid; Multi-resolution segmentation BibRef

Raveaux, R.[Romain], Martineau, M.[Maxime], Conte, D.[Donatello], Venturini, G.[Gilles],
Learning Graph Matching with a Graph-Based Perceptron in a Classification Context,
GbRPR17(49-58).
Springer DOI 1706
BibRef

Foggia, P.[Pasquale], Percannella, G.[Gennaro], Sansone, C.[Carlo], Vento, M.[Mario],
Benchmarking graph-based clustering algorithms,
IVC(27), No. 7, 4 June 2009, pp. 979-988.
Elsevier DOI 0904
BibRef
Earlier:
Assessing the Performance of a Graph-Based Clustering Algorithm,
GbRPR07(215-227).
Springer DOI 0706
Benchmarking; Graph-based clustering; Cluster detection BibRef

Massaro, A.[Alessio], Pelillo, M.[Marcello],
Matching graphs by pivoting,
PRL(24), No. 8, May 2003, pp. 1099-1106.
WWW Link. 0304
BibRef
Earlier:
A Complementary Pivoting Approach to Graph Matching,
EMMCVPR01(469-479).
Springer DOI 0205
BibRef

Luo, B.[Bin], Hancock, E.R.[Edwin R.], Wilson, R.C.[Richard C.],
Eigenspaces For Graphs,
IJIG(2), No. 2, April 2002, pp. 247-268. 0204
BibRef

Luo, B.[Bin], Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.],
Spectral embedding of graphs,
PR(36No. 10, October 2003, pp. 2213-2230.
WWW Link. 0308
BibRef
Earlier:
Graph spectral approach for learning view structure,
ICPR02(III: 785-788).
IEEE DOI 0211
BibRef

Wilson, R.C., Hancock, E.R.,
Levenshtein distance for graph spectral features,
ICPR04(II: 489-492).
IEEE DOI 0409
BibRef

Luo, B.[Bin], Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.],
A Spectral Approach to Learning Structural Variations in Graphs,
PR(39), No. 6, June 2006, pp. 1188-1198.
WWW Link. 0604
BibRef
Earlier: CVS03(407 ff).
Springer DOI 0306
BibRef
Earlier:
Learning modes of structural variation in graphs,
ICIP03(II: 37-40).
IEEE DOI 0312
BibRef
Earlier:
Spectral Clustering of Graphs,

Springer DOI 0311
Generative model; Graph; Covariance matrix; Clustering BibRef

Luo, B.[Bin], Wilson, R.C., Hancock, E.R.,
The independent and principal component of graph spectra,
ICPR02(II: 164-167).
IEEE DOI 0211
BibRef

Wilson, R.C.[Richard C.],
Graph Signatures for Evaluating Network Models,
ICPR14(100-105)
IEEE DOI 1412
Biological system modeling BibRef

Aziz, F.[Furqan], Hancock, E.R.[Edwin R.], Wilson, R.C.[Richard C.],
Graph Entropy from Closed Walk and Cycle Functionals,
SSSPR16(174-184).
Springer DOI 1611
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Ye, C.[Cheng], Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.],
An Entropic Edge Assortativity Measure,
GbRPR15(23-33).
Springer DOI 1511
BibRef
And:
Graph Characterization from Entropy Component Analysis,
ICPR14(3845-3850)
IEEE DOI 1412
BibRef
Earlier:
Entropic Graph Embedding via Multivariate Degree Distributions,
SSSPR14(163-172).
Springer DOI 1408
BibRef
And:
Heterogeneity Index for Directed Graphs,
CAIP13(II:424-431).
Springer DOI 1311
Complexity theory BibRef

Fu, Z.Y.[Zhou-Yu], Robles-Kelly, A.[Antonio],
An Energy Minimisation Approach to Attributed Graph Regularisation,
EMMCVPR07(71-86).
Springer DOI 0708
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Han, L.[Lin], Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.],
Generative Graph Prototypes from Information Theory,
PAMI(37), No. 10, October 2015, pp. 2013-2027.
IEEE DOI 1509
Complexity theory BibRef

Han, L.[Lin], Rossi, L.[Luca], Torsello, A.[Andrea], Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.],
Information Theoretic Prototype Selection for Unattributed Graphs,
SSSPR12(33-41).
Springer DOI 1211
BibRef

Luo, B.[Bin], Robles-Kelly, A.[Antonio], Torsello, A.[Andrea], Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.],
A Probabilistic Framework for Graph Clustering,
CVPR01(I:912-919).
IEEE DOI 0110
From set of distances between graphs characterize pairwise affinity. Culuster graphs. BibRef

Qiu, H.J.[Huai-Jun], Hancock, E.R.[Edwin R.],
Graph matching and clustering using spectral partitions,
PR(39), No. 1, January 2006, pp. 22-34.
WWW Link. 0512
BibRef
Earlier:
Spectral Simplification of Graphs,
ECCV04(Vol IV: 114-126).
Springer DOI 0405
BibRef

Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.], Luo, B.[Bin],
Pattern Vectors from Algebraic Graph Theory,
PAMI(27), No. 7, July 2005, pp. 1112-1124.
IEEE Abstract. 0506
BibRef
Earlier: A2, A3, A1:
Graph Pattern Spaces from Laplacian Spectral Polynomials,
ICIAR04(I: 327-334).
Springer DOI 0409
BibRef
Earlier: A1, A2, Only:
Pattern Spaces from Graph Polynomials,
CIAP03(480-485).
IEEE DOI 0310
Embed graphs in pattern space. BibRef

Han, L.[Lin], Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.], Bai, L.[Lu], Ren, P.[Peng],
Sampling graphs from a probabilistic generative model,
ICPR12(1643-1646).
WWW Link. 1302
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Falcao, A.X.[Alexandre X.], Stolfi, J.[Jorge], de Alencar Lotufo, R.[Roberto],
The Image Foresting Transform: Theory, Algorithms, and Applications,
PAMI(26), No. 1, January 2004, pp. 19-29.
IEEE Abstract. 0401
Graph-based design of image processing operators using connectivity. Minimum-cost path forest in a graph. BibRef

van Wyk, B.J.[Barend J.], and van Wyk, M.A.[Michael A.],
A POCS-Based Graph Matching Algorithm,
PAMI(26), No. 11, November 2004, pp. 1526-1530.
IEEE Abstract. 0410
Projections onto Convex Sets. Solve Attributed Graph Matching. BibRef

Wang, H.F.[Hong Fang], Hancock, E.R.[Edwin R.],
Correspondence matching using kernel principal components analysis and label consistency constraints,
PR(39), No. 6, June 2006, pp. 1012-1025.
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Earlier:
Improving Correspondence Matching Using Label Consistency Constraints,
IbPRIA05(I:235).
Springer DOI 0509
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And:
Kernel Spectral Correspondence Matching Using Label Consistency Constraints,
CIAP05(503-510).
Springer DOI 0509
Non-rigid motion; Correspondence matching; Graph spectral methods; Kernel PCA; Constraints BibRef

Bunke, H.[Horst], Dickinson, P.[Peter], Irniger, C.[Christophe], Kraetzl, M.[Miro],
Recovery of missing information in graph sequences by means of reference pattern matching and decision tree learning,
PR(39), No. 4, April 2006, pp. 573-586.
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Graph sequence analysis; Recovery of missing information; Computer network analysis; Machine learning; Decision tree classifier; Reference pattern matching BibRef

Bunke, H.[Horst], Irniger, C.[Christophe], Neuhaus, M.[Michel],
Graph Matching: Challenges and Potential Solutions,
CIAP05(1-10).
Springer DOI 0509
BibRef

Bunke, H.[Horst], Dickinson, P.[Peter], Kraetzl, M.[Miro],
Theoretical and Algorithmic Framework for Hypergraph Matching,
CIAP05(463-470).
Springer DOI 0509
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And:
Comparison of Two Different Prediction Schemes for the Analysis of Time Series of Graphs,
IbPRIA05(II:99).
Springer DOI 0509
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Huang, R.H.[Rui-Hong],
A Schedule-based Pathfinding Algorithm for Transit Networks Using Pattern First Search,
GeoInfo(11), No. 2, June 2007, pp. 269-285.
Springer DOI 0709
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Brun, L.[Luc], Escolano, F.[Francisco],
Graph-based Representations Preface,
IVC(27), No. 7, 4 June 2009, pp. 835-836.
Elsevier DOI 0904
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Bonev, B.[Boyan], Lozano, M.A.[Miguel A.], Escolano, F.[Francisco], Suau, P.[Pablo], Aguilar, W.[Wendy], Saez, J.M., Cazorla, M.A.[Miguel A.],
Region and constellations based categorization of images with unsupervised graph learning,
IVC(27), No. 7, 4 June 2009, pp. 960-978.
Elsevier DOI 0904
Image categorization; Clustering of graphs; EM algorithms BibRef
Earlier: A3, A2, A1, A4, A7, A5, Only:
Constellations and the Unsupervised Learning of Graphs,
GbRPR07(340-350).
Springer DOI 0706
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Romero, A.[Anna], Cazorla, M.A.[Miguel A.],
Topological SLAM Using Omnidirectional Images: Merging Feature Detectors and Graph-Matching,
ACIVS10(I: 464-475).
Springer DOI 1012
BibRef

Escolano, F.[Francisco], Liu, M.[Meizhu], Hancock, E.R.[Edwin R.],
Tensor-based total Bregman divergences between graphs,
ITCVPR11(1440-1447).
IEEE DOI 1201
BibRef

Escolano, F.[Francisco], Hancock, E.R.[Edwin R.],
Complexity Fusion for Indexing Reeb Digraphs,
CAIP13(120-127).
Springer DOI 1308
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And:
From Points to Nodes: Inverse Graph Embedding through a Lagrangian Formulation,
CAIP11(I: 194-201).
Springer DOI 1109
BibRef

Escolano, F.[Francisco], Hancock, E.R.[Edwin R.], Lozano, M.A.[Miguel A.],
Graph Similarity through Entropic Manifold Alignment,
SIIMS(10), No. 2, 2017, pp. 942-978.
DOI Link 1708
BibRef
Earlier:
Skeletal Graphs from Schrödinger Magnitude and Phase,
GbRPR15(335-344).
Springer DOI 1511
BibRef
Earlier:
Graph matching through entropic manifold alignment,
CVPR11(2417-2424).
IEEE DOI 1106
BibRef

Escolano, F.[Francisco], Bonev, B.[Boyan], Lozano, M.A.[Miguel A.],
Information-Geometric Graph Indexing from Bags of Partial Node Coverages,
GbRPR11(52-61).
Springer DOI 1105
BibRef

Bonev, B.[Boyan], Escolano, F.[Francisco], Giorgi, D.[Daniela], Biasotti, S.[Silvia],
Information-theoretic Feature Selection from Unattributed Graphs,
ICPR10(930-933).
IEEE DOI 1008
BibRef

Escolano, F.[Francisco], Lozano, M.A.[Miguel A.], Bonev, B.[Boyan], Suau, P.[Pablo],
Bypass information-theoretic shape similarity from non-rigid points-based alignment,
NORDIA10(37-44).
IEEE DOI 1006
BibRef

Escolano, F.[Francisco], Bonev, B.[Boyan], Hancock, E.R.[Edwin R.],
Heat Flow-Thermodynamic Depth Complexity in Directed Networks,
SSSPR12(190-198).
Springer DOI 1211
BibRef

Escolano, F.[Francisco], Curado, M.[Manuel], Biasotti, S.[Silvia], Hancock, E.R.[Edwin R.],
Shape Simplification Through Graph Sparsification,
GbRPR17(13-22).
Springer DOI 1706
BibRef

Fiorucci, M.[Marco], Torcinovich, A.[Alessandro], Curado, M.[Manuel], Escolano, F.[Francisco], Pelillo, M.[Marcello],
On the Interplay Between Strong Regularity and Graph Densification,
GbRPR17(165-174).
Springer DOI 1706
BibRef

Escolano, F.[Francisco], Curado, M.[Manuel], Lozano, M.A.[Miguel A.], Hancook, E.R.[Edwin R.],
Dirichlet Graph Densifiers,
SSSPR16(185-195).
Springer DOI 1611
BibRef

Escolano, F.[Francisco], Curado, M.[Manuel], Hancock, E.R.[Edwin R.],
Commute Times in Dense Graphs,
SSSPR16(241-251).
Springer DOI 1611
BibRef

Escolano, F.[Francisco], Lozano, M.A.[Miguel A.], Hancock, E.R.[Edwin R.],
Heat Flow-Thermodynamic Depth Complexity in Networks,
ICPR10(1578-1581).
IEEE DOI 1008
BibRef
Earlier: A1, A3, A2:
Birkhoff polytopes, heat kernels and graph complexity,
ICPR08(1-5).
IEEE DOI 0812
BibRef

Kokiopoulou, E.[Effrosyni], Frossard, P.[Pascal],
Minimum Distance between Pattern Transformation Manifolds: Algorithm and Applications,
PAMI(31), No. 7, July 2009, pp. 1225-1238.
IEEE DOI 0905
Transformation invariance. Minimum distance between the transformation manifolds spanned by patterns of interest. BibRef

Kokiopoulou, E.[Effrosyni], Kressner, D., Frossard, P.[Pascal],
Optimal Image Alignment With Random Projections of Manifolds: Algorithm and Geometric Analysis,
IP(20), No. 6, June 2011, pp. 1543-1557.
IEEE DOI 1106
BibRef

Kokiopoulou, E.[Effrosyni], Frossard, P.[Pascal],
Graph-based classification of multiple observation sets,
PR(43), No. 12, December 2010, pp. 3988-3997.
Elsevier DOI 1003
BibRef
And:
Distributed classification of multiple observations by consensus,
ICIP10(2697-2700).
IEEE DOI 1009
Graph-based classification; Multiple observations sets; Video face recognition; Multi-view object recognition BibRef

Kokiopoulou, E.[Effrosyni], Pirillos, S.[Stefanos], Frossard, P.[Pascal],
Graph-based classification for multiple observations of transformed patterns,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Lezoray, O.[Olivier], Ta, V.T.[Vinh-Thong], El Moataz, A.[Abderrahim],
Partial differences as tools for filtering data on graphs,
PRL(31), No. 14, 15 October 2010, pp. 2201-2213.
Elsevier DOI 1003
Partial difference equations; Weighted graphs; Mathematical morphology; Anisotropic and isotropic discrete regularization BibRef

Leordeanu, M.[Marius], Sukthankar, R.[Rahul], Hebert, M.[Martial],
Unsupervised Learning for Graph Matching,
IJCV(96), No. 1, January 2012, pp. 28-45.
WWW Link. 1201
BibRef

Leordeanu, M.[Marius], Hebert, M.[Martial],
Unsupervised learning for graph matching,
CVPR09(864-871).
IEEE DOI 0906
BibRef

Leordeanu, M.[Marius],
Spectral Graph Matching, Learning, and Inference for Computer Vision,
CMU-RI-TR-09-27, July, 2009. BibRef 0907 Ph.D.Thesis, Carnegie Mellon University, July, 2009.
WWW Link. 1102
BibRef

Leordeanu, M.[Marius], Hebert, M.[Martial],
A Spectral Technique for Correspondence Problems Using Pairwise Constraints,
ICCV05(II: 1482-1489).
IEEE DOI 0510
BibRef

Leordeanu, M.[Marius], Hebert, M.[Martial],
Pairwise Grouping Using Color,
CMU-RI-TR-08-46, December, 2008.
WWW Link. BibRef 0812

Leordeanu, M.[Marius], Hebert, M.[Martial], Sukthankar, R.[Rahul],
Beyond Local Appearance: Category Recognition from Pairwise Interactions of Simple Features,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Leordeanu, M.[Marius], Zanfir, A.[Andrei], Sminchisescu, C.[Cristian],
Locally Affine Sparse-to-Dense Matching for Motion and Occlusion Estimation,
ICCV13(1721-1728)
IEEE DOI 1403
Feature Matching BibRef

Leordeanu, M.[Marius], Zanfir, A.[Andrei], Sminchisescu, C.[Cristian],
Semi-supervised learning and optimization for hypergraph matching,
ICCV11(2274-2281).
IEEE DOI 1201
BibRef

Tang, J.[Jin], Jiang, B.[Bo], Zheng, A.[Aihua], Luo, B.[Bin],
Graph matching based on spectral embedding with missing value,
PR(45), No. 10, October 2012, pp. 3768-3779.
Elsevier DOI 1206
Dot product representation of graph; Missing value; Association graph; Co-embedding; Point pattern matching BibRef

Jiang, B.[Bo], Zhao, H.F.[Hai-Feng], Tang, J.[Jin], Luo, B.[Bin],
A sparse nonnegative matrix factorization technique for graph matching problems,
PR(47), No. 2, 2014, pp. 736-747.
Elsevier DOI 1311
Graph matching BibRef

Jiang, B.[Bo], Tang, J.[Jin], Cao, X.C.[Xiao-Chun], Luo, B.[Bin],
Lagrangian relaxation graph matching,
PR(61), No. 1, 2017, pp. 255-265.
Elsevier DOI 1609
Graph matching BibRef

Jiang, B.[Bo], Tang, J.[Jin], Zheng, A.[Aihua], Luo, B.[Bin],
Image representation and matching with geometric-edge random structure graph,
PRL(87), No. 1, 2017, pp. 20-28.
Elsevier DOI 1703
Image representation BibRef

Jiang, B.[Bo], Tang, J.[Jin], Ding, C., Luo, B.[Bin],
Binary Constraint Preserving Graph Matching,
CVPR17(550-557)
IEEE DOI 1711
BibRef
Earlier: A1, A2, A4, Only:
Attributed Relational Graph Matching with Sparse Relaxation and Bistochastic Normalization,
GbRPR15(218-227).
Springer DOI 1511
BibRef
Earlier: A2, A1, A4, Only:
Graph Matching Based on Dot Product Representation of Graphs,
GbRPR11(175-184).
Springer DOI 1105
Computational modeling, Convergence, Pattern recognition, Projection algorithms, Quadratic programming. BibRef

Prakash, S.[Surya], Robles-Kelly, A.[Antonio],
Geometric graph comparison from an alignment viewpoint,
PR(45), No. 10, October 2012, pp. 3780-3794.
Elsevier DOI 1206
Graph comparison and retrieval; Graph algorithms; Graph theory BibRef

Takaoka, A.[Asahi], Tayu, S.[Satoshi], Ueno, S.[Shuichi],
On Minimum Feedback Vertex Sets in Bipartite Graphs and Degree-Constraint Graphs,
IEICE(E96-D), No. 11, November 2013, pp. 2327-2332.
WWW Link. 1311
BibRef

Wang, J.M., Chen, S.W., Fuh, C.S.,
Attributed hypergraph matching on a Riemannian manifold,
MVA(25), No. 4, May 2014, pp. 823-844.
WWW Link. 1404
BibRef

Lagraa, S.[Sofiane], Seba, H.[Hamida], Khennoufa, R.[Riadh], M'Baya, A.[Abir], Kheddouci, H.[Hamamache],
A distance measure for large graphs based on prime graphs,
PR(47), No. 9, 2014, pp. 2993-3005.
Elsevier DOI 1406
Graph similarity BibRef

Leng, C.C.[Cheng-Cai], Xu, W.[Wei], Cheng, I., Basu, A.,
Graph Matching Based on Stochastic Perturbation,
IP(24), No. 12, December 2015, pp. 4862-4875.
IEEE DOI 1512
eigenvalues and eigenfunctions BibRef

Vogelstein, J.T., Roncal, W.G., Vogelstein, R.J., Priebe, C.E.,
Graph Classification Using Signal-Subgraphs: Applications in Statistical Connectomics,
PAMI(35), No. 7, 2013, pp. 1539-1551.
IEEE DOI medical signal processing; graph classification; Brain modeling 1307
BibRef

Lyzinski, V., Fishkind, D.E., Fiori, M., Vogelstein, J.T., Priebe, C.E., Sapiro, G.,
Graph Matching: Relax at Your Own Risk,
PAMI(38), No. 1, January 2016, pp. 60-73.
IEEE DOI 1601
Bismuth. BibRef

Chen, L., Shen, C., Vogelstein, J.T., Priebe, C.E.[Carey E.],
Robust Vertex Classification,
PAMI(38), No. 3, March 2016, pp. 578-590.
IEEE DOI 1602
Analytical models BibRef

Zhang, H.Y.[Heng-Yuan], Chen, X.W.[Xiao-Wu], Li, J.[Jia], Zhou, B.[Bin],
Fuzzy community detection via modularity guided membership-degree propagation,
PRL(70), No. 1, 2016, pp. 66-72.
Elsevier DOI 1602
Fuzzy community detection BibRef

Savage, N.[Neil],
Graph Matching in Theory and Practice,
CACM(59), No. 7, July 2016, pp. 12-14.
DOI Link 1608
New algorithm for graph isomorphism. See also Graph Isomorphism in Quasipolynomial Time. BibRef

Wang, T.[Tao], Ling, H.B.[Hai-Bin], Lang, C.Y.[Cong-Yan], Feng, S.[Songhe],
Symmetry-aware graph matching,
PR(60), No. 1, 2016, pp. 657-668.
Elsevier DOI 1609
Symmetry BibRef

Chen, R.[Ran], Lang, C.Y.[Cong-Yan], Wang, T.[Tao],
Multiple path exploration for graph matching,
MVA(28), No. 7, October 2017, pp. 695-703.
WWW Link. 1710
singular point discovering by checking the smoothness of the path. BibRef

Park, H.M.[Han-Mu], Yoon, K.J.[Kuk-Jin],
Encouraging second-order consistency for multiple graph matching,
MVA(27), No. 7, October 2016, pp. 1021-1034.
Springer DOI 1610
BibRef

Abu-Aisheh, Z.[Zeina],
Anytime and Distributed Approaches for Graph Matching,
ELCVIA(15), No. 2, 2016, pp. 13-15.
DOI Link 1611
BibRef

Abu-Aisheh, Z.[Zeina], Raveaux, R.[Romain], Ramel, J.Y.[Jean-Yves],
Anytime graph matching,
PRL(84), No. 1, 2016, pp. 215-224.
Elsevier DOI 1612
BibRef
Earlier:
A Graph Database Repository and Performance Evaluation Metrics for Graph Edit Distance,
GbRPR15(138-147).
Springer DOI 1511
Graph matching BibRef

Zhang, H.[He], Ren, P.[Peng],
Game theoretic hypergraph matching for multi-source image correspondences,
PRL(87), No. 1, 2017, pp. 87-95.
Elsevier DOI 1703
Hypergraph matching BibRef

Zhang, H.[He], Du, B.[Bin], Wang, Y.J.[Yan-Jiang], Ren, P.[Peng],
A Hypergraph Matching Framework for Refining Multi-source Feature Correspondences,
GbRPR15(108-117).
Springer DOI 1511
BibRef

Wang, Z.S.[Zhen-Sheng], Yue, Y.[Yang], Li, Q.Q.[Qing-Quan], Nie, K.[Ke], Yu, C.B.[Chang-Bin],
Analysis of the Spatial Variation of Network-Constrained Phenomena Represented by a Link Attribute Using a Hierarchical Bayesian Model,
IJGI(6), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Nguyen, Q.[Quynh], Tudisco, F.[Francesco], Gautier, A.[Antoine], Hein, M.[Matthias],
An Efficient Multilinear Optimization Framework for Hypergraph Matching,
PAMI(39), No. 6, June 2017, pp. 1054-1075.
IEEE DOI 1705
Algorithm design and analysis, Approximation algorithms, Computer vision, Optimization, Pattern matching, Tensile stress, Three-dimensional displays, Hypergraph Matching, block coordinate ascent, multilinear form, tensor BibRef

Ngoc, Q.N.[Quynh Nguyen], Gautier, A.[Antoine], Hein, M.[Matthias],
A flexible tensor block coordinate ascent scheme for hypergraph matching,
CVPR15(5270-5278)
IEEE DOI 1510
BibRef

Zhuang, L.S.[Lian-Sheng], Zhou, Z.H.[Zi-Han], Gao, S.H.[Sheng-Hua], Yin, J.W.[Jing-Wen], Lin, Z.C.[Zhou-Chen], Ma, Y.[Yi],
Label Information Guided Graph Construction for Semi-Supervised Learning,
IP(26), No. 9, September 2017, pp. 4182-4192.
IEEE DOI 1708
convex programming, graph theory, knowledge representation, learning (artificial intelligence), convex optimization problem, graph-based semi-supervised learning, label information guided graph construction, label propagation, linearized alternating direction method, self-representation graph learning, semi-supervised low-rank representation, Convex functions, Data models, Data structures, Manifolds, Robustness, Semisupervised learning, Label information, low-rank representation, semi-supervised graph learning BibRef

Jansen, A.[Aren], Sell, G.[Gregory], Lyzinski, V.[Vince],
Scalable out-of-sample extension of graph embeddings using deep neural networks,
PRL(94), No. 1, 2017, pp. 1-6.
Elsevier DOI 1708
Deep neural networks BibRef


Allili, M.[Madjid], Kaczynski, T.[Tomasz], Landi, C.[Claudia], Masoni, F.[Filippo],
Algorithmic Construction of Acyclic Partial Matchings for Multidimensional Persistence,
DGCI17(375-387).
Springer DOI 1711
BibRef

Salim, A.[Asif], Shiju, S.S., Sumitra, S.,
Effectiveness of Representation and Length Variation of Shortest Paths in Graph Classification,
PReMI17(509-516).
Springer DOI 1711
BibRef

Lê-Huu, D.K.[D. Khuê], Paragios, N.[Nikos],
Alternating Direction Graph Matching,
CVPR17(4914-4922)
IEEE DOI 1711
Convex functions, Linear programming, Pattern matching, Tensile, stress BibRef

Swoboda, P., Rother, C., Alhaija, H.A., Kainmüller, D., Savchynskyy, B.,
A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching,
CVPR17(7062-7071)
IEEE DOI 1711
Labeling, Message passing, Optimization, Pattern matching, Schedules BibRef

Tang, M.[Min], Wang, W.M.[Wen-Min],
Progressive Probabilistic Graph Matching with Local Consistency Regularization,
CAIP17(II: 105-115).
Springer DOI 1708
BibRef

Song, D.B.[Dao-Bang], Zhang, J.W.[Jiu-Wen], Zhou, J.[Jing],
Case study for graph signal denoising by graph structure similarity,
ICIVC17(847-851)
IEEE DOI 1708
Additives, Gaussian noise, Noise measurement, Partitioning algorithms, Silicon carbide, community detection, denoising, graph signal processing, graph structure similarity, image modeling. BibRef

Santacruz, P.[Pep], Algabli, S.[Shaima], Serratosa, F.[Francesc],
Node Matching Computation Between Two Large Graphs in Linear Computational Cost,
GbRPR17(143-153).
Springer DOI 1706
BibRef

Rossi, L.[Luca], Severini, S.[Simone], Torsello, A.[Andrea],
The Average Mixing Matrix Signature,
SSSPR16(474-484).
Springer DOI 1611
signatures for graphs, used for matching. BibRef

Lockhart, J.[Joshua], Minello, G.[Giorgia], Rossi, L.[Luca], Severini, S.[Simone], Torsello, A.[Andrea],
Edge Centrality via the Holevo Quantity,
SSSPR16(143-152).
Springer DOI 1611
most important edge. BibRef

Wang, T.[Tao], Ling, H.B.[Hai-Bin], Lang, C.[Congyan], Wu, J.[Jun],
Branching Path Following for Graph Matching,
ECCV16(II: 508-523).
Springer DOI 1611
BibRef

De Ita, G.[Guillermo], Bello, P.[Pedro], Contreras, M.[Meliza], Catana-Salazar, J.C.[Juan C.],
Efficient Counting of the Number of Independent Sets on Polygonal Trees,
MCPR16(167-176).
Springer DOI 1608
BibRef

Yu, T., Wang, R.,
Graph matching with low-rank regularization,
WACV16(1-9)
IEEE DOI 1606
Linear matrix inequalities BibRef

Ye, C.[Cheng], Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.],
Correlation Network Evolution Using Mean Reversion Autoregression,
SSSPR16(163-173).
Springer DOI 1611
BibRef

Minello, G.[Giorgia], Torsello, A.[Andrea], Hancock, E.R.[Edwin R.],
Quantum thermodynamics of time evolving networks,
ICPR16(1536-1541)
IEEE DOI 1705
BibRef
And:
Thermodynamic Characterization of Temporal Networks,
SSSPR16(49-59).
Springer DOI 1611
Correlation, Eigenvalues and eigenfunctions, Energy exchange, Entropy, Laplace equations, Stock markets, Thermodynamics BibRef

Ye, C.[Cheng], Torsello, A.[Andrea], Wilson, R.C.[Richard C.], Hancock, E.R.[Edwin R.],
Thermodynamics of Time Evolving Networks,
GbRPR15(315-324).
Springer DOI 1511
BibRef

Oskarsson, M.[Magnus], Astrom, K.[Kalle], Torstensson, A.[Anna],
Prime Rigid Graphs and Multidimensional Scaling with Missing Data,
ICPR14(750-755)
IEEE DOI 1412
Bipartite graph BibRef

Brimkov, B.[Boris],
On Sets of Line Segments Featuring a Cactus Structure,
IWCIA17(30-39).
Springer DOI 1706
BibRef
Earlier:
Memory Efficient Shortest Path Algorithms for Cactus Graphs,
ISVC13(I:476-485).
Springer DOI 1310
BibRef

Raetz, W.,
A new approach to graph analysis for activity based intelligence,
AIPR12(1-8)
IEEE DOI 1307
graph theory BibRef

Ji, Y.M.[Yi-Ming], Yu, C.[Changbin], Anderson, B.D.O.,
Threshold phenomenon for average consensus,
ICARCV12(548-553).
IEEE DOI 1304
BibRef

Suh, Y.[Yumin], Cho, M.[Minsu], Lee, K.M.[Kyoung Mu],
Graph Matching via Sequential Monte Carlo,
ECCV12(III: 624-637).
Springer DOI 1210
BibRef

Yan, J.C.[Jun-Chi], Zhang, C.[Chao], Zha, H.Y.[Hong-Yuan], Liu, W.[Wei], Yang, X.K.[Xiao-Kang], Chu, S.M.[Stephen M.],
Discrete hyper-graph matching,
CVPR15(1520-1528)
IEEE DOI 1510
BibRef

Yan, J.C.[Jun-Chi], Tian, Y.[Yu], Zha, H.Y.[Hong-Yuan], Yang, X.K.[Xiao-Kang], Zhang, Y.[Ya], Chu, S.M.[Stephen M.],
Joint Optimization for Consistent Multiple Graph Matching,
ICCV13(1649-1656)
IEEE DOI 1403
BibRef

Tian, Y.[Yu], Yan, J.C.[Jun-Chi], Zhang, H.Q.[He-Quan], Zhang, Y.[Ya], Yang, X.K.[Xiao-Kang], Zha, H.Y.[Hong-Yuan],
On the Convergence of Graph Matching: Graduated Assignment Revisited,
ECCV12(III: 821-835).
Springer DOI 1210
BibRef

De Ita Luna, G.[Guillermo], Marcial-Romero, J.R.[J. Raymundo],
Computing #2SAT and #2UNSAT by Binary Patterns,
MCPR12(273-282).
Springer DOI 1208
Combinatorics. BibRef

Pacheco, A.[Ana], Real, P.[Pedro],
An Efficient Algorithm to Compute Subsets of Points in Zn,
CTIC12(58-67).
Springer DOI 1206
BibRef

Liu, J.G.[Jin-Gen], Ali, S.[Saad],
Learning Scene Semantics Using Fiedler Embedding,
ICPR10(3627-3630).
IEEE DOI 1008
BibRef

Chen, W.F.[Wei-Fu], Feng, G.C.[Guo-Can],
Semi-supervised Graph Learning: Near Strangers or Distant Relatives,
ICPR10(3368-3371).
IEEE DOI 1008
BibRef

Swiderski, R.[Rafal], Strug, B.[Barbara],
Using Parallel Graph Transformations in Design Support System,
ICCVG10(II: 309-316).
Springer DOI 1009
BibRef

Chen, M.[Mo], Liu, M.[Ming], Liu, J.Z.[Jian-Zhuang], Tang, X.[Xiaoou],
Isoperimetric cut on a directed graph,
CVPR10(2109-2116).
IEEE DOI Video of talk:
WWW Link. 1006
BibRef

Ishikawa, H.[Hiroshi],
Higher-order gradient descent by fusion-move graph cut,
ICCV09(568-574).
IEEE DOI 0909
BibRef
And:
Higher-order clique reduction in binary graph cut,
CVPR09(2993-3000).
IEEE DOI 0906
BibRef

Srihari, S.[Sriganesh], Ng, H.K.[Hoong Kee], Ning, K.[Kang], Leong, H.W.[Hon Wai],
Detecting hubs and quasi cliques in scale-free networks,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Le, T.V.[Thang V.], Kulikowski, C.A.[Casimir A.], Muchnik, I.B.[Ilya B.],
Coring method for clustering a graph,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Yaghi, H., Krim, H.,
Probabilistic graph matching by canonical decomposition,
ICIP08(2368-2371).
IEEE DOI 0810
BibRef

El Ghawalby, H.[Hewayda], Hancock, E.R.[Edwin R.],
Characterizing Graphs Using Spherical Triangles,
IbPRIA09(465-472).
Springer DOI 0906
BibRef
And:
Graph Regularisation Using Gaussian Curvature,
GbRPR09(233-242).
Springer DOI 0905
BibRef
Earlier:
Graph Characteristic from the Gauss-Bonnet Theorem,
SSPR08(207-216).
Springer DOI 0812
BibRef
Earlier:
Measuring Graph Similarity Using Spectral Geometry,
ICIAR08(xx-yy).
Springer DOI 0806
BibRef

Haxhimusa, Y.[Yll], Kropatsch, W.G.[Walter G.], Pizlo, Z.[Zygmunt], Ion, A.[Adrian], Lehrbaum, A.[Andreas],
Approximating TSP Solution by MST Based Graph Pyramid,
GbRPR07(295-306).
Springer DOI 0706
Travelling saleseman. BibRef

Suvonvorn, N.[Nikom], Zavidovique, B.[Bertrand],
A Stable Marriages Algorithm to Optimize Satisfaction and Equity,
ICIAR06(II: 422-433).
Springer DOI 0610
BibRef

de Piero, F.W.[Fred W.], Carlin, J.K.[John K.],
Structural Matching Via Optimal Basis Graphs,
ICPR06(III: 449-452).
IEEE DOI 0609
BibRef

de Piero, F.W.,
Structural graph matching with polynomial bounds on memory and on worst-case effort,
ICPR04(III: 379-382).
IEEE DOI 0409
BibRef

Kropatsch, W.G.[Walter G.], Haxhimusa, Y.[Yll],
Grouping of Non-connected Structures by an Irregular Graph Pyramid,
IbPRIA05(II:107).
Springer DOI 0509
BibRef

Haxhimusa, Y., Glantz, R., Saib, M., Langs, G., Kropatsch, W.G.,
Logarithmic Tapering Graph Pyramid,
DAGM02(117 ff.).
Springer DOI 0303
BibRef

Giugno, R., Shasha, D.,
GraphGrep: a fast and universal method for querying graphs,
ICPR02(II: 112-115).
IEEE DOI 0211
BibRef

Hlaoui, A., Wang, S.R.[Sheng-Rui],
A new algorithm for inexact graph matching,
ICPR02(IV: 180-183).
IEEE DOI 0211
BibRef

Bunke, H.,
Recent Developments in Graph Matching,
ICPR00(Vol II: 117-124).
IEEE DOI 0009
BibRef

Rizzi, S.[Stefano],
A Genetic Approach to Hierarchical Clustering of Euclidean Graphs,
ICPR98(Vol II: 1543-1545).
IEEE DOI 9808
BibRef

Kotzer, T., Cohen, N., Shamir, J.,
Generalized approach to projections onto convex constraint sets,
ICPR94(C:77-81).
IEEE DOI 9410
BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
General Structure and Graph Representation and Matching, Relations, Neighbors .


Last update:Dec 7, 2017 at 17:23:10