Abstract
Abstract:
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.