In this paper a novel method called Extended TwoDimensional PCA (E2DPCA) is proposed which is an extension to the original 2DPCA. We state that the covariance matrix of 2DPCA is e...
Mehran Safayani, Mohammad Taghi Manzuri Shalmani, ...
The two-dimensional Principal Component Analysis (2DPCA) is a robust method in face recognition. Much recent research shows that the 2DPCA is more reliable than the well-known PCA ...
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional d...
Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. Recently, LDA has been extended to...
We discuss a new multi-view face recognition method that extends a recently proposed nonlinear tensor decomposition technique. We use this technique to provide a generative face m...