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N. Hu, R. Rustamov, and L. Guibas, Stable and Informative Spectral Signatures for Graph Matching, CVPR2014
Abstract:
In this paper, we consider the approximate weighted graph matching
problem and introduce stable and informative first and second order
compatibility terms suitable for inclusion into the popular integer
quadratic program formulation. Our approach relies on a rigorous analysis
of stability of spectral signatures based on the graph Laplacian.
In the case of the first order term, we derive an objective function
that measures both the stability and informativeness of a given spectral
signature. By optimizing this objective, we design new spectral node
signatures tuned to a specific graph to be matched. We also introduce
the pairwise heat kernel distance as a stable second order compatibility
term; we justify its plausibility by showing that in a certain limiting
case it converges to the classical adjacency matrix-based second order
compatibility function. We have tested our approach on a set of synthetic
graphs, the widely-used CMU house sequence, and a set of real images.
These experiments show the superior performance of our first and second
order compatibility terms as compared with the commonly used ones.
Bibtex:
@article{hrg-sissgm-2014,
author = {Nan Hu and Raif Rustamov and Leonidas Guibas},
title = {Stable and Informative Spectral Signatures for Graph Matching},
journal = {CVPR},
year = {2014},
}
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