Improving graph matching via density maximization

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dc.contributor.authorWang, Chao
dc.contributor.authorWang, Lei
dc.contributor.authorLiu, Lingqiao
dc.coverage.spatialSydney Australia
dc.date.accessioned2015-12-10T23:08:49Z
dc.date.createdDecember 1-8 2013
dc.date.issued2013
dc.date.updated2015-12-10T09:08:54Z
dc.description.abstractGraph matching has been widely used in various applications in computer vision due to its powerful performance. However, it poses three challenges to image sparse feature matching: (1) The combinatorial nature limits the size of the possible matches, (2)
dc.identifier.isbn9781479930227
dc.identifier.urihttp://hdl.handle.net/1885/63267
dc.publisherIEEE
dc.relation.ispartofseries2013 14th IEEE International Conference on Computer Vision Workshops, ICCVW 2013
dc.sourceProceedings of the IEEE International Conference on Computer Vision
dc.titleImproving graph matching via density maximization
dc.typeConference paper
local.bibliographicCitation.lastpage3431
local.bibliographicCitation.startpage3424
local.contributor.affiliationWang, Chao, University of Wollongong
local.contributor.affiliationWang, Lei, University of Wollongong
local.contributor.affiliationLiu, Lingqiao, College of Engineering and Computer Science, ANU
local.contributor.authoremailrepository.admin@anu.edu.au
local.contributor.authoruidLiu, Lingqiao, u4629919
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080309 - Software Engineering
local.identifier.ariespublicationU3488905xPUB787
local.identifier.doi10.1109/ICCV.2013.425
local.identifier.scopusID2-s2.0-84898817782
local.identifier.uidSubmittedByU3488905
local.type.statusPublished Version

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