Exploiting multi-layer graph factorization for multi-attributed graph matching

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dc.contributor.authorPark, Han-Muko
dc.contributor.authorYoon, Kuk-Jinko
dc.date.accessioned2019-11-18T05:20:03Z-
dc.date.available2019-11-18T05:20:03Z-
dc.date.created2018-09-28-
dc.date.issued2019-11-
dc.identifier.citationPATTERN RECOGNITION LETTERS, v.127, pp.85 - 93-
dc.identifier.issn0167-8655-
dc.identifier.urihttp://hdl.handle.net/10203/268435-
dc.description.abstractMulti-layer graph matching methods effectively solve multi-attributed graph matching problems based on the multi-layer structure adopted to address the ambiguity and uncertainty arisen from the attribute integration. However, despite of its effectiveness for matching multi-attributed graphs, the approach has a long way to apply in the practical environment due to the scalability problem caused by a huge matrix for describing the multi-layer structure. In this paper, we propose a novel multi-layer graph matching algorithm based on the multi-layer graph factorization to address the issue. The main contribution of this research is three-fold. First, we propose a factorization method that decomposes the huge multi-layer matrix into several small matrices for efficiency. Second, we reformulate the original multi-layer matching problem into two relaxed problems by using the factorized matrices. Third, based on the relaxed problems, we propose a multi-layer graph matching algorithm inspired from the convex-concave relaxation procedure. In our extensive experiments on the synthetic and real-image datasets, the proposed method exhibits better performance than state-of-the-art algorithms based on the single-layer structure.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE BV-
dc.titleExploiting multi-layer graph factorization for multi-attributed graph matching-
dc.typeArticle-
dc.identifier.wosid000493892700011-
dc.identifier.scopusid2-s2.0-85054583654-
dc.type.rimsART-
dc.citation.volume127-
dc.citation.beginningpage85-
dc.citation.endingpage93-
dc.citation.publicationnamePATTERN RECOGNITION LETTERS-
dc.identifier.doi10.1016/j.patrec.2018.09.024-
dc.contributor.localauthorYoon, Kuk-Jin-
dc.contributor.nonIdAuthorPark, Han-Mu-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorMulti-attributed graph matching-
dc.subject.keywordAuthorMulti-layer structure-
dc.subject.keywordAuthorMatrix factorization-
dc.subject.keywordAuthorPath following-
dc.subject.keywordPlusASSIGNMENT-
dc.subject.keywordPlusCOMPUTATION-
dc.subject.keywordPlusALGORITHM-
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