Heterogeneous Techniques used in Face Recognition: A Survey

Face Recognition has become one of the important areas of research in computer vision. Human Communication is a combination of both verbal and non-verbal. For interaction in the society, face serve as the primary canvas used to express distinct emotions non-verbally. The face of one person provides the most important natural means of communication. In this paper, we will discuss the various works done in the area of face recognition where focus is on intelligent approaches like PCA, LDA, DFLD, SVD, GA etc. In the current trend, combination of these existing techniques are being taken into consideration and are discussed in this paper.Keywords: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Genetic Algorithm (GA), Direct Fractional LDA (DFLD

Face Recognition using R-KDA with Non-Linear SVM for Multi-View Database

AbstractThis paper develops a new Face Recognition System which combines R-KDA for selecting optimal discriminant features with non-linear SVM for Recognition. Experiment results have been conducted showing the comparison of enhanced efficiency of our proposed system over R-KDA with k-nn as the similarity distance measure