DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Han-Mu | ko |
dc.contributor.author | Yoon, Kuk-Jin | ko |
dc.date.accessioned | 2019-11-18T05:20:03Z | - |
dc.date.available | 2019-11-18T05:20:03Z | - |
dc.date.created | 2018-09-28 | - |
dc.date.created | 2018-09-28 | - |
dc.date.issued | 2019-11 | - |
dc.identifier.citation | PATTERN RECOGNITION LETTERS, v.127, pp.85 - 93 | - |
dc.identifier.issn | 0167-8655 | - |
dc.identifier.uri | http://hdl.handle.net/10203/268435 | - |
dc.description.abstract | Multi-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.language | English | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.title | Exploiting multi-layer graph factorization for multi-attributed graph matching | - |
dc.type | Article | - |
dc.identifier.wosid | 000493892700011 | - |
dc.identifier.scopusid | 2-s2.0-85054583654 | - |
dc.type.rims | ART | - |
dc.citation.volume | 127 | - |
dc.citation.beginningpage | 85 | - |
dc.citation.endingpage | 93 | - |
dc.citation.publicationname | PATTERN RECOGNITION LETTERS | - |
dc.identifier.doi | 10.1016/j.patrec.2018.09.024 | - |
dc.contributor.localauthor | Yoon, Kuk-Jin | - |
dc.contributor.nonIdAuthor | Park, Han-Mu | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Multi-attributed graph matching | - |
dc.subject.keywordAuthor | Multi-layer structure | - |
dc.subject.keywordAuthor | Matrix factorization | - |
dc.subject.keywordAuthor | Path following | - |
dc.subject.keywordPlus | ASSIGNMENT | - |
dc.subject.keywordPlus | COMPUTATION | - |
dc.subject.keywordPlus | ALGORITHM | - |
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