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NIPS
2004
13 years 8 months ago
Two-Dimensional Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional d...
Jieping Ye, Ravi Janardan, Qi Li
ICIP
2006
IEEE
14 years 8 months ago
Fusion of Visible and Infrared Images using Empirical Mode Decomposition to Improve Face Recognition
In this effort, we propose a new image fusion technique, utilizing Empirical Mode Decomposition (EMD), for improved face recognition. EMD is a non-parametric datadriven analysis t...
Harishwaran Hariharan, Andreas Koschan, Besma R. A...
PRL
2002
146views more  PRL 2002»
13 years 6 months ago
Face recognition with one training image per person
: Recently, a method called (PC)2 A was proposed to deal with face recognition with one training image per person. As an extension of the standard eigenface technique, (PC)2 A comb...
Jianxin Wu, Zhi-Hua Zhou
ISNN
2005
Springer
14 years 6 days ago
An Improvement on PCA Algorithm for Face Recognition
Principle Component Analysis (PCA) technique is an important and well-developed area of image recognition and to date many linear discrimination methods have been put forward. Desp...
Vo Dinh Minh Nhat, Sungyoung Lee
CVPR
2005
IEEE
14 years 8 months ago
Subspace Analysis Using Random Mixture Models
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
Xiaogang Wang, Xiaoou Tang