| A Tensor-Based Algorithm for High-Order Graph Matching. | |
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MedLine Citation:
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PMID: 21646677 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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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. |
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Authors:
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Olivier Duchenne; Francis Bach; In-So Kweon; Jean Ponce |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-5-26 |
Journal Detail:
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Title: IEEE transactions on pattern analysis and machine intelligence Volume: - ISSN: 1939-3539 ISO Abbreviation: - Publication Date: 2011 May |
Date Detail:
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Created Date: 2011-6-7 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9885960 Medline TA: IEEE Trans Pattern Anal Mach Intell Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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École Normale Supérieure de Paris and the Willow project team (CNRS/ENS/INRIA UMR 8548). |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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