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Pattern Recognition, International Conference on (2006)
Hong Kong
Aug. 20, 2006 to Aug. 24, 2006
ISSN: 1051-4651
ISBN: 0-7695-2521-0
pp: 666-669
HongFang Wang , University of York, York, UK
Edwin R. Hancock , University of York, York, UK
ABSTRACT
In this paper a new formulation of probabilistic relaxation labeling is developed using the theory of diffusion processes on graphs. According to this picture, the label probabilities are given by the state-vector of a continuous time random walk on a support graph. The state-vector is the solution of the heat equation on the support-graph. The nodes of the support graph are the Cartesian product of the object-set and label-set of the relaxation process. The compatibility functions are combined in the weight matrix of the support graph. The solution of the heat-equation is found by exponentiating the eigensystem of the Laplacian matrix for the weighted support graph with time. We demonstrate the new relaxation process on a feature correspondence matching problem abstracted in terms of relational graphs.
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CITATION

H. Wang and E. R. Hancock, "Probabilistic Relaxation using the Heat Equation," 2006 18th International Conference on Pattern Recognition(ICPR), Hong Kong, 2006, pp. 666-669.
doi:10.1109/ICPR.2006.947
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