Abstract
This paper describes how graph-spectral methods can be used to transform the node correspondence problem into one of point-set alignment. We commence by using a heat kernel analysis to compute geodesic distances between nodes in the graphs. With geodesic distances to hand, we use the ISOMAP algorithm to embed the nodes of a graph in a low-dimensional Euclidean space. With the nodes in the graph transformed to points in a metric space, we can recast the problem of graph-matching into that of aligning the points. Here we use a variant of the Scott and Longuet-Higgins algorithm to find point correspondences. We experiment with the resulting algorithm on a number of real-world problems.
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Xiao, B., Yu, H., Hancock, E. (2004). Graph Matching Using Manifold Embedding. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_44
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DOI: https://doi.org/10.1007/978-3-540-30125-7_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23223-0
Online ISBN: 978-3-540-30125-7
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