Boosting Dissociated Region Pair LDA for Face Recognition
Yong Gao, Yangsheng Wang · 2006
We propose a novel face recognition algorithm based on dissociated region pair linear discriminant analysis (DRP-LDA). Given a training set, LDA is applied to every dissociated region pair of face images. The DRP-LDA features are obtained by projecting corresponding regions into subspace. Then classifier is constructed based on the features with appropriate distance measure. Multiple classifiers like this are combined together by weighted sum rule. Both regions and weights are learned by AdaBoost algorithm. Experimental results on FERET face databases show an impressive accuracy of our algorithm compared with conventional and component-based LDA methods.