Subspace learning based face recognition methods have attracted considerable interests in recently years, including Principal Component Analysis (PCA), Linear Discriminant Analysi...
Deng Cai, Xiaofei He, Yuxiao Hu, Jiawei Han, Thoma...
In this paper, we propose a novel method, called local nonnegative matrix factorization (LNMF), for learning spatially localized, parts-based subspace representation of visual pat...
Stan Z. Li, XinWen Hou, HongJiang Zhang, QianSheng...
In this paper, we study the problem of subspace-based face recognition under scenarios with spatial misalignments and/or image occlusions. For a given subspace, the embedding of a...
Huan Wang, Shuicheng Yan, Thomas S. Huang, Jianzhu...
Outdoor face recognition is among the most challenging problems for face recognition. In this paper, we develop a discriminant mutual subspace learning algorithm for indoor and ou...
In this paper, we systematically study the effect of poorly registered faces on the training and inferring stages of traditional face recognition algorithms. We then propose a nov...