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» Components for Face Recognition
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ICPR
2004
IEEE
16 years 5 months ago
Support Vector Machine with Local Summation Kernel for Robust Face Recognition
This paper presents Support Vector Machine (SVM) with local summation kernel for robust face recognition. In recent years, the effectiveness of SVM and local features is reported....
Kazuhiro Hotta
ICB
2009
Springer
140views Biometrics» more  ICB 2009»
15 years 10 months ago
A Discriminant Analysis Method for Face Recognition in Heteroscedastic Distributions
Linear discriminant analysis (LDA) is a popular method in pattern recognition and is equivalent to Bayesian method when the sample distributions of different classes are obey to t...
Zhen Lei, ShengCai Liao, Dong Yi, Rui Qin, Stan Z....
FGR
2006
IEEE
117views Biometrics» more  FGR 2006»
15 years 10 months ago
A Landmark Paper in Face Recognition
Good registration (alignment to a reference) is essential for accurate face recognition. The effects of the number of landmarks on the mean localization error and the recognition ...
G. M. Beumer, Qian Tao, Asker M. Bazen, Raymond N....
AMFG
2005
IEEE
164views Biometrics» more  AMFG 2005»
15 years 6 months ago
Pose-Encoded Spherical Harmonics for Robust Face Recognition Using a Single Image
Abstract. Face recognition under varying pose is a challenging problem, especially when illumination variations are also present. Under Lambertian model, spherical harmonics repres...
Zhanfeng Yue, Wenyi Zhao, Rama Chellappa
ICCV
2007
IEEE
15 years 10 months ago
Laplacian PCA and Its Applications
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
Deli Zhao, Zhouchen Lin, Xiaoou Tang