In this paper we address the problem of simultaneously matching multiple graphs imposing cyclic or transitive consistency among the correspondences. This is obtained through a synchronization process that projects doubly-stochastic matrices onto a consistent set. We overcome the lack of group structure of the Birkhoff polytope, i.e., the space of doubly-stochastic matrices, by making use the Birkhoff-Von Neumann theorem stating that any doubly-stochastic matrix can be seen as the expectation of a distribution over the permutation matrices, and then cast the synchronization problem as one over the underlying permutations. This allows us to transform any graph-matching algorithm working on the Birkhoff polytope into a multi-graph matching algorithm. We evaluate the performance of two classic graph matching algorithms in their synchronized and un-synchronized versions with a state-of-the-art multi-graph matching approach, showing that synchronization can yield better and more robust matches.

Synchronization over the Birkhoff polytope for multi-graph matching

SCHIAVINATO, MICHELE;TORSELLO, Andrea
2017-01-01

Abstract

In this paper we address the problem of simultaneously matching multiple graphs imposing cyclic or transitive consistency among the correspondences. This is obtained through a synchronization process that projects doubly-stochastic matrices onto a consistent set. We overcome the lack of group structure of the Birkhoff polytope, i.e., the space of doubly-stochastic matrices, by making use the Birkhoff-Von Neumann theorem stating that any doubly-stochastic matrix can be seen as the expectation of a distribution over the permutation matrices, and then cast the synchronization problem as one over the underlying permutations. This allows us to transform any graph-matching algorithm working on the Birkhoff polytope into a multi-graph matching algorithm. We evaluate the performance of two classic graph matching algorithms in their synchronized and un-synchronized versions with a state-of-the-art multi-graph matching approach, showing that synchronization can yield better and more robust matches.
2017
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3691320
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