—We address the problem of comparing sets of images for object recognition, where the sets may represent variations in an object’s appearance due to changing camera pose and li...
In this paper, we propose an ICA(Indepdendent Component Analysis) based face recognition algorithm, which is robust to illumination and pose variation. Generally, it is well known...
Tae-Kyun Kim, Hyunwoo Kim, Wonjun Hwang, Seok-Cheo...
Subspace learning based face recognition methods have attracted considerable interests in recent years, including Principal Component Analysis (PCA), Linear Discriminant Analysis ...
Abstract. Illumination variation is one of intractable yet crucial problems in face recognition and many lighting normalization approaches have been proposed in the past decades. N...
Hu Han, Shiguang Shan, Laiyun Qing, Xilin Chen, We...
We propose a new approach for face recognition under arbitrary illumination conditions, which requires only one training image per subject (if there is no pose variation) and no 3...