Comparison of principal component analysis and linear discriminant analysis for face recognition (March 2007)
P. E. Robinson · 2007
In this paper two face recognition techniques, principal component analysis (PCA) and linear discriminant analysis (LDA), are considered and implemented using a nearest neighbor classifier. The performance of the two techniques is then compared in facial recognition and detection tasks. The comparisons are done using a facial recognition database captured for the project that contains images captured over a range of poses, lighting conditions and occlusions.