Discriminant feature extraction and selection for person-independent facial expression recognition
dc.contributor.author | Xue, Mingliang | |
dc.contributor.supervisor | Assoc. Prof. Wanquan Liu | |
dc.contributor.supervisor | Assoc. Prof. Ling Li | |
dc.contributor.supervisor | Assoc. Prof. Ajmal Mian | |
dc.date.accessioned | 2017-01-30T10:18:03Z | |
dc.date.available | 2017-01-30T10:18:03Z | |
dc.date.created | 2015-08-07T02:04:08Z | |
dc.date.issued | 2015 | |
dc.identifier.uri | http://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.language | en | |
dc.publisher | Curtin University | |
dc.title | Discriminant feature extraction and selection for person-independent facial expression recognition | |
dc.type | Thesis | |
dcterms.educationLevel | PhD | |
curtin.department | Department of Computing | |
curtin.accessStatus | Open access |