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dc.contributor.authorDahm, Nicholas
dc.contributor.authorGao, Yongsheng
dc.contributor.authorCaelli, Terry
dc.contributor.authorBunke, Horst
dc.contributor.editorIEEE
dc.date.accessioned2017-05-03T14:13:09Z
dc.date.available2017-05-03T14:13:09Z
dc.date.issued2013
dc.date.modified2014-04-22T04:51:22Z
dc.identifier.isbn9781479923410
dc.identifier.issn1522-4880
dc.identifier.refurihttp://www.ieeeicip.org/
dc.identifier.doi10.1109/ICIP.2013.6738700
dc.identifier.urihttp://hdl.handle.net/10072/58724
dc.description.abstractLocalising and aligning objects is a challenging task in computer vision that still remains largely unsolved. Utilising the syntactic power of graph representation, we define a relational string-graph matching algorithm that seeks to perform these tasks simultaneously. By matching the relations between vertices, where vertices represent high-level primitives, the relational string-graph is able to overcome the noisy and inconsistent nature of the vertices themselves. For each possible relation correspondence between two graphs, we calculate the rotation, translation, and scale parameters required to transform a relation into its counterpart. We plot these parameters in 4D space and use Gaussian mixture models and the expectation-maximisation algorithm to estimate the underlying parameters. Our method is tested on face alignment and recognition, but is equally (if not more) applicable for generic object alignment.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.publisherIEEE
dc.publisher.placeUnited States
dc.relation.ispartofstudentpublicationY
dc.relation.ispartofconferencename20th IEEE International Conference on Image Processing (ICIP)
dc.relation.ispartofconferencetitle2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013)
dc.relation.ispartofdatefrom2013-09-15
dc.relation.ispartofdateto2013-09-18
dc.relation.ispartoflocationMelbourne, AUSTRALIA
dc.relation.ispartofpagefrom3394
dc.relation.ispartofpageto3398
dc.rights.retentionY
dc.subject.fieldofresearchPattern Recognition and Data Mining
dc.subject.fieldofresearchComputer Vision
dc.subject.fieldofresearchcode080109
dc.subject.fieldofresearchcode080104
dc.titleMatching Non-aligned Objects using a Relational String-graph
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, Griffith School of Engineering
gro.date.issued2013
gro.hasfulltextNo Full Text
gro.griffith.authorGao, Yongsheng
gro.griffith.authorDahm, Nicholas


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    Contains papers delivered by Griffith authors at national and international conferences.

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