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A tensor-based algorithm for high-order graph matching

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4 Author(s)
Duchenne, O. ; Ecole Normale Super. de Paris, Paris, France ; Bach, F. ; Kweon, I. ; Ponce, J.

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.

Published in:

Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on

Date of Conference:

20-25 June 2009