At present, there are many methods for frontal view face recognition. However, few of them can work well when only one example image per class is available. In this paper, we pres...
The null space N(St) of total scatter matrix St contains no useful information for pattern classification. So, discarding the null space N(St) results in dimensionality reduction ...
Wen-Sheng Chen, Pong Chi Yuen, Jian Huang, Jian-Hu...
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 ...
Previous works have demonstrated that the face recognition performance can be improved significantly in low dimensional linear subspaces. Conventionally, principal component analy...
In this paper we present a novel approach of face identification by formulating the pattern recognition problem in terms of linear regression. Using a fundamental concept that pat...