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Issue No.04 - April (2004 vol.26)
pp: 515-519
<p><b>Abstract</b>—In this paper, we show how inexact graph matching (that is, the correspondence between <it>sets</it> of vertices of pairs of graphs) can be solved using the renormalization of projections of the vertices (as defined in this case by their connectivities) into the joint eigenspace of a pair of graphs and a form of relational clustering. An important feature of this eigenspace renormalization projection clustering (EPC) method is its ability to match graphs with different number of vertices. Shock graph-based shape matching is used to illustrate the model and a more objective method for evaluating the approach using random graphs is explored with encouraging results.</p>
Inexact multisubgraph matching, eigendecomposition, eigenspace projections, correspondence clustering, shape matching, random graphs.
Terry Caelli, Serhiy Kosinov, "An Eigenspace Projection Clustering Method for Inexact Graph Matching", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.26, no. 4, pp. 515-519, April 2004, doi:10.1109/TPAMI.2004.1265866
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