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» Scale-robust Feature Extraction For Face Recognition
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ICPR
2008
IEEE
14 years 2 months ago
Pose adaptive LDA based face recognition
In this paper, a novel method based on pose adaptive linear discriminant analysis (PALDA) is proposed to deal with pose variation problems in face recognition when each person has...
Zhenger Wang, Xiaoqing Ding, Chi Fang
CVPR
2005
IEEE
14 years 7 months ago
A Framework of 2D Fisher Discriminant Analysis: Application to Face Recognition with Small Number of Training Samples
A novel framework called 2D Fisher Discriminant Analysis (2D-FDA) is proposed to deal with the Small Sample Size (SSS) problem in conventional One-Dimensional Linear Discriminan...
Hui Kong, Lei Wang, Eam Khwang Teoh, Jian-Gang Wan...
CVPR
2009
IEEE
15 years 2 months ago
Implicit Elastic Matching with Random Projections for Pose-variant Face Recognition
We present a new approach to robust pose-variant face recognition, which exhibits excellent generalization ability even across completely different datasets due to its weak depe...
John Wright (University of Illinois), Gang Hua (Mi...
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 ...
ICMLA
2007
13 years 9 months ago
Scalable optimal linear representation for face and object recognition
Optimal Component Analysis (OCA) is a linear method for feature extraction and dimension reduction. It has been widely used in many applications such as face and object recognitio...
Yiming Wu, Xiuwen Liu, Washington Mio