Symbolic Image Matching by Simulated AnnealingReport as inadecuate




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1 CEA-LETI - Laboratoire d-Electronique et des Technologies de l-Information 2 LIFIA - Laboratoire d-Informatique Fondamentale et d-Intelligence Artificielle 3 MOVI - Modeling, localization, recognition and interpretation in computer vision GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71

Abstract : In this paper we suggest an optimisation approach to visual matching. We assume that the information available in an image may be conveniently represented symbolically in a relational graph. We concentrate on the problem of matching two such graphs. First we derive a cost function associated with graph matching and more precisely associated with subgraph isomorphism and with maximum subgraph matching. This cost function is well suited for optimization methods such as simulated annealing. We show how the graph matching problem is easily cast into a simulated annealing algorithm. Finally we show some preliminary experimental results and discuss the utility of this graph matching method in computer vision in general.





Author: Laurent Hérault - Radu Horaud - Françoise Veillon - Jean-Jacques Niez -

Source: https://hal.archives-ouvertes.fr/



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