Graph matching by neural relaxation |
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Authors: | M Turner J Austin |
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Affiliation: | (1) Department of Computer Science, University of York, York, UK |
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Abstract: | We propose a new relaxation scheme for graph matching in computer vision. The main distinguishing feature of our approach is that matching is formulated as a process of eliminating unlikely candidates rather than finding the best match directly. Bayesian development leads to a robust algorithm which can be implemented in a fast and efficient manner on a neural network architecture. We illustrate the utility of the technique through comparisons with its conventional counterpart on simulated and real-world data. |
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Keywords: | Correlation matrix memories Graph matching Relaxation labelling |
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