This paper proposes a novel nonlinear discriminant analysis method named by Kernerlized Maximum Average Margin Criterion (KMAMC), which has combined the idea of Support Vector Mac...
In this paper we propose a two-dimensional (2D) Laplacianfaces method for face recognition. The new algorithm is developed based on two techniques, i.e., locality preserved embedd...
Ben Niu, Qiang Yang, Simon Chi-Keung Shiu, Sankar ...
It is well-known that the applicability of Linear Discriminant Analysis (LDA) to high-dimensional pattern classification tasks such as face recognition (FR) often suffers from the...
Juwei Lu, Konstantinos N. Plataniotis, Anastasios ...
: Applications such as Face Recognition (FR) that deal with high-dimensional data need a mapping technique that introduces representation of low-dimensional features with enhanced ...
This paper is focused on algorithmic issues for biometric face verification (i.e., given an image of the face and an identity claim, decide whether they correspond to each other o...
Javier Ortega-Garcia, Joaquin Gonzalez-Rodriguez, ...