Graph matching based on mean field theory
2010 IEEE International Conference on Image Processing, 2010•ieeexplore.ieee.org
In this paper, we propose a new graph matching algorithm based on mean field theory. We
first convert the original graph matching problem which is a quadratic integer programming
problem to a spin model with quadratic interaction by dropping the matching constraints.
Then the matching constraints are added to the system iteratively after each round of mean
field calculation. Prominent matching pairs found in previous iterations will guide the mean
field calculation in the next round. Experiments on the CMU house dataset and a CTC …
first convert the original graph matching problem which is a quadratic integer programming
problem to a spin model with quadratic interaction by dropping the matching constraints.
Then the matching constraints are added to the system iteratively after each round of mean
field calculation. Prominent matching pairs found in previous iterations will guide the mean
field calculation in the next round. Experiments on the CMU house dataset and a CTC …
In this paper, we propose a new graph matching algorithm based on mean field theory. We first convert the original graph matching problem which is a quadratic integer programming problem to a spin model with quadratic interaction by dropping the matching constraints. Then the matching constraints are added to the system iteratively after each round of mean field calculation. Prominent matching pairs found in previous iterations will guide the mean field calculation in the next round. Experiments on the CMU house dataset and a CTC dataset show promising matching results.
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