On the application of the probabilistic linear discriminant analysis to face recognition across expression
Wibowo, Moh Edi, Tjondronegoro, Dian W., & Zhang, Ligang (2012) On the application of the probabilistic linear discriminant analysis to face recognition across expression. In 2012 IEEE International Conference on Multimedia and Expo Workshops, IEEE Computer Society, Melbourne, Australia, pp. 459-464.
Facial expression is one of the main issues of face recognition in uncontrolled environments. In this paper, we apply the probabilistic linear discriminant analysis (PLDA) method to recognize faces across expressions. Several PLDA approaches are tested and cross-evaluated on the Cohn-Kanade and JAFFE databases. With less samples per gallery subject, high recognition rates comparable to previous works have been achieved indicating the robustness of the approaches. Among the approaches, the mixture of PLDAs has demonstrated better performances. The experimental results also indicate that facial regions around the cheeks, eyes, and eyebrows are more discriminative than regions around the mouth, jaw, chin, and nose.
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|Item Type:||Conference Paper|
|Keywords:||face recognition, expression-invariant, probabilistic linear discriminant analysis|
|Divisions:||Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2012 IEEE Computer Society|
|Copyright Statement:||2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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|Deposited On:||02 Oct 2012 23:17|
|Last Modified:||05 Oct 2012 04:11|
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