… Face detection is nothing but to search for human faces in digital images and if … an emotion
recognition system using facial feature extraction with the help of PCA and LDA as facial …

… In this article, we tested the use of a data mining … As such, a linear discriminant analysis (LDA)
algorithm was … by using artificial features computed through principal component analysis (…

… for facial recognition is the linear discriminant analysis (LDA)… a face and principal component
analysis for face recognition. … and Principle component analysis results in quick detection …

… Face recognition is a very important application of LDA, which has been extensively
studied over the last two decades. In order to deal with the singularity problem of the within-class …

… This section will discuss the results attained using PCA and LDA as feature extraction
followed by classification. Note that upon frame normalization, 30 frames are set for each walking …

… Linear Discriminant Analysis (LDA) is used as the dimension reduction step in this procedure.
The LDA … projection (LPP) [50], principle component analysis (PCA), etc. can be gathered …

… , such as illumination, facial expression, or shooting angle. … software framework for PCA-based
face recognition aimed at … the complete process of PCA-based face recognition, and in …

… Recall that the linear discriminant analysis (LDA) is another powerful … the discriminant
vectors to maximize the ratio of the between-class distance to the within-class distance. Since LDA …

… [23] were the first to introduce a 2D linear discriminant analysis algorithm. However, Li
and Yuan proposed 2D-LDA [12] showing better discriminant features [33]. Wang et al. [25] …

… Two-dimensional linear discriminant analysis (2DLDA) is a widely applied extension of
LDA that can cope with matrix input samples directly. However, its construction is based on a …