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ICMCS
2006
IEEE
160views Multimedia» more  ICMCS 2006»
14 years 2 months ago
Selecting Kernel Eigenfaces for Face Recognition with One Training Sample Per Subject
It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
Jie Wang, Konstantinos N. Plataniotis, Anastasios ...
ICIP
2002
IEEE
14 years 10 months ago
A kernel machine based approach for multi-view face recognition
Techniques that can introduce low-dimensional feature representation with enhanced discriminatory power is of paramount importance in face recognition applications. It is well kno...
Juwei Lu, Kostas N. Plataniotis, Anastasios N. Ven...
JMM2
2008
157views more  JMM2 2008»
13 years 8 months ago
Multiresolution Feature Based Fractional Power Polynomial Kernel Fisher Discriminant Model for Face Recognition
This paper presents a technique for face recognition which uses wavelet transform to derive desirable facial features. Three level decompositions are used to form the pyramidal mul...
Dattatray V. Jadhav, Jayant V. Kulkarni, Raghunath...
AMFG
2005
IEEE
152views Biometrics» more  AMFG 2005»
14 years 2 months ago
Regularization of LDA for Face Recognition: A Post-processing Approach
When applied to high-dimensional classification task such as face recognition, linear discriminant analysis (LDA) can extract two kinds of discriminant vectors, those in the null s...
Wangmeng Zuo, Kuanquan Wang, David Zhang, Jian Yan...
PR
2002
122views more  PR 2002»
13 years 8 months ago
High-order Fisher's discriminant analysis
This paper introduces a novel nonlinear extension of Fisher's classical linear discriminant analysis (FDA) known as high-order Fisher's discriminant analysis (HOFDA). Th...
Alejandro Sierra