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» A Landmark Paper in Face Recognition
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PR
2008
87views more  PR 2008»
13 years 7 months ago
Two-dimensional Laplacianfaces method for face recognition
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 ...
PR
2010
170views more  PR 2010»
13 years 6 months ago
Sparsity preserving projections with applications to face recognition
: Dimensionality reduction methods (DRs) have commonly been used as a principled way to understand the high-dimensional data such as face images. In this paper, we propose a new un...
Lishan Qiao, Songcan Chen, Xiaoyang Tan
TIP
2011
137views more  TIP 2011»
13 years 2 months ago
Boosting Color Feature Selection for Color Face Recognition
—This paper introduces the new color face recognition (FR) method that makes effective use of boosting learning as color-component feature selection framework. The proposed boost...
Jae Young Choi, Yong Man Ro, Konstantinos N. Plata...
ICCV
2011
IEEE
12 years 7 months ago
Sparse Representation or Collaborative Representation: Which Helps Face Recognition?
As a recently proposed technique, sparse representation based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse lin...
Lei Zhang, Meng Yang, Xiangchu Feng
CVPR
2005
IEEE
14 years 9 months ago
Representational Oriented Component Analysis (ROCA) for Face Recognition with One Sample Image per Training Class
Subspace methods such as PCA, LDA, ICA have become a standard tool to perform visual learning and recognition. In this paper we propose Representational Oriented Component Analysi...
Fernando De la Torre, Ralph Gross, Simon Baker, B....