Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/111984
Citations
Scopus Web of Science® Altmetric
?
?
Full metadata record
DC FieldValueLanguage
dc.contributor.authorZulqarnain Gilani, S.en
dc.contributor.authorMian, A.en
dc.contributor.authorShafait, F.en
dc.contributor.authorReid, I.en
dc.date.issued2018en
dc.identifier.citationIEEE Transactions on Pattern Analysis and Machine Intelligence, 2018; 40(7):1584-1598en
dc.identifier.issn0162-8828en
dc.identifier.issn2160-9292en
dc.identifier.urihttp://hdl.handle.net/2440/111984-
dc.description.abstractWe present an algorithm that automatically establishes dense correspondences between a large number of 3D faces. Starting from automatically detected sparse correspondences on the outer boundary of 3D faces, the algorithm triangulates existing correspondences and expands them iteratively by matching points of distinctive surface curvature along the triangle edges. After exhausting keypoint matches, further correspondences are established by generating evenly distributed points within triangles by evolving level set geodesic curves from the centroids of large triangles. A deformable model (K3DM) is constructed from the dense corresponded faces and an algorithm is proposed for morphing the K3DM to fit unseen faces. This algorithm iterates between rigid alignment of an unseen face followed by regularized morphing of the deformable model. We have extensively evaluated the proposed algorithms on synthetic data and real 3D faces from the FRGCv2, Bosphorus, BU3DFE and UND Ear databases using quantitative and qualitative benchmarks. Our algorithm achieved dense correspondences with a mean localisation error of 1.28mm on synthetic faces and detected 14 anthropometric landmarks on unseen real faces from the FRGCv2 database with 3mm precision. Furthermore, our deformable model fitting algorithm achieved 98.5% face recognition accuracy on the FRGCv2 and 98.6% on Bosphorus database. Our dense model is also able to generalize to unseen datasets.en
dc.description.statementofresponsibilitySyed Zulqarnain Gilani, Ajmal Mian, Faisal Shafait, and Ian Reiden
dc.language.isoenen
dc.publisherIEEEen
dc.rights© 2017 IEEEen
dc.subjectDense correspondence; 3D face; morphing; keypoint detection; level sets; geodesic curves; deformable modelen
dc.titleDense 3D Face Correspondenceen
dc.typeJournal articleen
dc.identifier.rmid0030082891en
dc.identifier.doi10.1109/TPAMI.2017.2725279en
dc.relation.granthttp://purl.org/au-research/grants/arc/DP110102399en
dc.identifier.pubid365814-
pubs.library.collectionComputer Science publicationsen
pubs.library.teamDS03en
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidReid, I. [0000-0001-7790-6423]en
Appears in Collections:Computer Science publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.