Show simple item record

dc.contributor.authorXue, Mingliang
dc.contributor.supervisorAssoc. Prof. Wanquan Liu
dc.contributor.supervisorAssoc. Prof. Ling Li
dc.contributor.supervisorAssoc. Prof. Ajmal Mian
dc.date.accessioned2017-01-30T10:18:03Z
dc.date.available2017-01-30T10:18:03Z
dc.date.created2015-08-07T02:04:08Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/20.500.11937/2159
dc.description.abstract

This thesis is to develop new facial expression recognition techniques based on 2D/3D images or videos, with the purpose to improve the recognition efficiency and accuracy of the current state-of-art. A fully automatic facial expression recognition system is designed, including real-time landmark detection, spatio-temporal feature extraction, hierarchical classification, and most discriminant facial regions identification for expression recognition. In general, the proposed system improved the facial expression recognition state-of-art.

dc.languageen
dc.publisherCurtin University
dc.titleDiscriminant feature extraction and selection for person-independent facial expression recognition
dc.typeThesis
dcterms.educationLevelPh.D.
curtin.departmentDepartment of Computing
curtin.accessStatusOpen access


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record