FACIAL IMAGE FEATURE EXTRACTION USING SUPPORT VECTOR MACHINES
Hamid Abrishami Moghaddam, Mehdi Ghayoumi · 2006
In this paper, we present an approach that unifies sub-space feature extraction and support vector classification for face recognition. Linear discriminant, independent component and principal component analyses are used for dimensionality reduction prior to introducing feature vectors to a support vector machine. The performance of the developed methods in reducing classification error and providing better generalization for high dimensional face recognition application is demonstrated.