… Face recognition performances using the ICA representations were benchmarked by …
that face recognition performance improved with the number of components separated. We …

… in different conditions of face orientation. In this research, Principal component analysis
approach to the face recognition problem was studied and a face recognition system based on …

… In our experiments, for the FacE REcognition Technology (FERET) [38] dataset, face detection
is based on manual detection of the centers of the eyes, and for the ORL dataset,1 no face …

… building of face recognition system by using Principal Component Analysis (PCA) method.
PCA is a statistical approach used for reducing the number of variables in face recognition. …

… The most representative recognition techniques frequently used in conjunction with face
recognition are principal component analysis (PCA) [1], independent component analysis (ICA) […

… considered a generalization of principal component analysis (PCA). … face recognition
problem. Experiments were made on two different face databases, achieving very high recognition …

… A novel face recognition method called diagonal principal component analysis (DiaPCA) is
… The essential idea of the proposed method is to generate the diagonal face images from the …

… of face images based on independent component analysis (ICA) … component analysis (PCA)
for recognizing faces across changes in lighting and changes in pose. For each set of face …

… Analysis, Discrete … Component Analysis (PCA) method for face recognition in an efficient
manner. There are numerous issues to take into account whenever choosing a face recognition …

… A number of face recognition algorithms employ principal component analysis (PCA), which
is … components analysis for recognizing faces across days and changes in expression. …