Facial Expression Recognition Using Two-Class Discriminant Features

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Facial Expression Recognition Using Two-Class Discriminant Features
This paper presents a novel facial expression recognition methodology. In order to classify the expression of a test face to one of seven pre-determined facial expression classes, multiple two-class classification tasks are carried out. For each such task, a unique set of features is identified that is enhanced, in terms of its ability to help produce a proper separation between the two specific classes. The selection of these sets of features is accomplished by making use of a class separability measure that is utilized in an iterative process. Fisher's linear discriminant is employed in order to produce the separation between each pair of classes and train each two-class classifier. In order to combine the classification results from all two-class classifiers, the `voting' classifier-decision fusion process is employed. The standard JAFFE database is utilized in order to evaluate the performance of this algorithm. Experimental results show that the proposed methodology prov...
Marios Kyperountas, Ioannis Pitas
Added 17 Feb 2011
Updated 17 Feb 2011
Type Journal
Year 2009
Where COST
Authors Marios Kyperountas, Ioannis Pitas
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