2001 StructuralGraphMatchingUsingEMandSVD

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Subject Headings: Graph Matching Task, Graph Distance Function, EM Algorithm, Matrix Factorization, Mixture Model, Delaunay Triangulation, Singular Value Decomposition.

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Abstract

This paper describes an efficient algorithm for inexact graph matching. The method is purely structural, that is, it uses only the edge or connectivity structure of the graph and does not draw on node or edge attributes. We make two contributions: 1) commencing from a probability distribution for matching errors, we show how the problem of graph matching can be posed as maximum-likelihood estimation using the apparatus of the EM algorithm; and 2) we cast the recovery of correspondence matches between the graph nodes in a matrix framework. This allows one to efficiently recover correspondence matches using the singular value decomposition. We experiment with the method on both real-world and synthetic data. Here, we demonstrate that the method offers comparable performance to more computationally demanding methods


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2001 StructuralGraphMatchingUsingEMandSVDBin Luo
Edwin R. Hancock
Structural Graph Matching Using the EM Algorithm and Singular Value DecompositionIEEE Transactions on Pattern Analysis and Machine Intelligencehttp://www.aprs.org.au/accv2002/accv2002 proceedings/Luo75.pdf10.1109/34.9546022001