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dc.contributor.authorFan, Ke
dc.contributor.supervisorAssoc. Prof. Ling Li
dc.contributor.supervisorProf. Wan-Quan Liu
dc.contributor.supervisorAssoc. Prof. Ajmal Mian
dc.date.accessioned2017-01-30T10:21:02Z
dc.date.available2017-01-30T10:21:02Z
dc.date.created2016-01-06T01:19:19Z
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/20.500.11937/2378
dc.description.abstract

We propose a novel framework to solve the face recognition problem base on set of testing images. Our framework can handle the case that no pose overlap between training set and query set. The main techniques used in this framework are manifold alignment, face normalization and discriminant learning. Experiments on different databases show our system outperforms some state of the art methods.

dc.languageen
dc.publisherCurtin University
dc.titleA framework of face recognition with set of testing images
dc.typeThesis
dcterms.educationLevelPhD
curtin.departmentDepartment of Computing
curtin.accessStatusOpen access


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