Illumination invariance remains the most researched, yet the most challenging aspect of automatic face recognition. In this paper we propose a novel, general recognition framework...
In this paper we present a fusion technique for Support Vector Machine (SVM) scores, obtained after a dimension reduction with Bilateralprojection-based Two-Dimensional Principal C...
Images constitute data that lives in a very high dimensional space, typically of the order of hundred thousand dimensions. Drawing inferences from data of such high dimensions soon...
This paper proposes a general method for improving image descriptors using discriminant projections. Two methods based on Linear Discriminant Analysis have been recently introduce...
Gabor feature has been widely recognized as one of the best representations for face recognition. However, traditionally, it has to be reduced in dimension due to curse of dimensi...