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dc.contributor.authorMai, Lam-
dc.contributor.authorPhan, Trong Thanh-
dc.descriptionScientific Paper; Pages: 39-48vi_VN
dc.description.abstractIn this paper, we propose a new approach to facial expression recognition based on the constrained non-negative matrix factorization algorithm. Our proposed method incorporated two tasks in an automatic expression analysis system: facial feature extraction and classification into expressions. To obtain local and geometric structure information in the data as much as possible, we unite max-margin classification into the constrained NMF optimization, resulting in a multiplicative updating algorithm is also proposed for solving optimization problem. Experimental results on JAFFE dataset demonstrate that the effectiveness of the proposed method with improved performances over the conventional dimension reduction methods.vi_VN
dc.publisherDa Nang Publishing Housevi_VN
dc.subjectfacial expressionsvi_VN
dc.subjectnonnegative matrix factorizationvi_VN
dc.subjectgraph regularizationvi_VN
dc.subjectspatial constraintsvi_VN
dc.titleJoint Spatial Geometric and Max-margin Classifier Constraints for Facial Expression Recognition Using Nonnegative Matrix Factorizationvi_VN
dc.typeWorking Papervi_VN
Appears in Collections:CITA 2019

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