We present a new approach, called local discriminant embedding (LDE), to manifold learning and pattern classification. In our framework, the neighbor and class relations of data a...
Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn fea...
Shuang-Hong Yang, Hongyuan Zha, Shaohua Kevin Zhou...
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 ...
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...
Non-negative matrix factorization (NMF) is a powerful feature extraction method for finding parts-based, linear representations of non-negative data . Inherently, it is unsupervis...