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A Tensor-Based Algorithm for High-Order Graph Matching
Abstract : This paper addresses the problem of establishing correspondences between two sets of visual features using higher-order constraints instead of the unary or pairwise ones used in classical methods. Concretely, the corresponding hypergraph matching problem is formulated as the maximization of a multilinear objective function over all permutations of the features. This function is defined by a tensor representing the affinity between feature tuples. It is maximized using a generalization of spectral techniques where a relaxed problem is first solved by a multi-dimensional power method, and the solution is then projected onto the closest assignment matrix. The proposed approach has been implemented, and it is compared to state-of-the-art algorithms on both synthetic and real data.
Cited literature [29 references]
https://hal.inria.fr/hal-01063322
Contributor : Suha Kwak <>
Submitted on : Thursday, September 11, 2014 - 5:39:07 PM
Last modification on : Tuesday, May 4, 2021 - 2:06:02 PM
Long-term archiving on: : Friday, December 12, 2014 - 10:56:44 AM
Contributor : Suha Kwak <>
Submitted on : Thursday, September 11, 2014 - 5:39:07 PM
Last modification on : Tuesday, May 4, 2021 - 2:06:02 PM
Long-term archiving on: : Friday, December 12, 2014 - 10:56:44 AM
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duchennePAMI2011.pdf
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