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Synchronisation of partial multi-matchings via non-negative factorisations
MPI Informatics, Saarland Informatics Campus, Saarbrücken, Germany.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0002-9738-4148
LCSB, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
MPI Informatics, Saarland Informatics Campus, Saarbrücken, Germany.
2019 (English)In: Pattern Recognition, ISSN 0031-3203, E-ISSN 1873-5142, Vol. 92, p. 146-155Article in journal (Refereed) Published
Abstract [en]

In this work we study permutation synchronisation for the challenging case of partial permutations, which plays an important role for the problem of matching multiple objects (e.g. images or shapes). The term synchronisation refers to the property that the set of pairwise matchings is cycle-consistent, i.e. in the full matching case all compositions of pairwise matchings over cycles must be equal to the identity. Motivated by clustering and matrix factorisation perspectives of cycle-consistency, we derive an algo- rithm to tackle the permutation synchronisation problem based on non-negative factorisations. In order to deal with the inherent non-convexity of the permutation synchronisation problem, we use an initialisation procedure based on a novel rotation scheme applied to the solution of the spectral relaxation. Moreover, this rotation scheme facilitates a convenient Euclidean projection to obtain a binary solution after solving our relaxed problem. In contrast to state-of-the-art methods, our approach is guaranteed to produce cycle-consistent results. We experimentally demonstrate the efficacy of our method and show that it achieves better results compared to existing methods. © 2019 Elsevier Ltd

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2019. Vol. 92, p. 146-155
Keywords [en]
multi-matching, matrix factorization, permutation synchronization, computer vision
National Category
Computer Sciences Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:hh:diva-39449DOI: 10.1016/j.patcog.2019.03.021Scopus ID: 2-s2.0-85063620765OAI: oai:DiVA.org:hh-39449DiVA, id: diva2:1317357
Note

This work was funded by the ERC Starting Grant CapReal ( 335545 ), the ERC Consolidator Grant 4DRepLy ( 770784 ), and by the Luxembourg National Research Fund (FNR, C14/BM/8231540 ).

Available from: 2019-05-22 Created: 2019-05-22 Last updated: 2019-05-28Bibliographically approved

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Thunberg, Johan

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