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» Components for Face Recognition
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AUSAI
2005
Springer
15 years 5 months ago
Resampling LDA/QR and PCA+LDA for Face Recognition
Abstract. Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) prob...
Jun Liu, Songcan Chen
ICPR
2004
IEEE
16 years 26 days ago
Illumination and Expression Invariant Face Recognition with One Sample Image
Most face recognition approaches either assume constant lighting condition or standard facial expressions, thus cannot deal with both kinds of variations simultaneously. This prob...
Brian C. Lovell, Shaokang Chen
99
Voted
PRL
2002
146views more  PRL 2002»
14 years 11 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
PAMI
2006
227views more  PAMI 2006»
14 years 11 months ago
Matching 2.5D Face Scans to 3D Models
The performance of face recognition systems that use two-dimensional images depends on factors such as lighting and subject's pose. We are developing a face recognition system...
Xiaoguang Lu, Anil K. Jain, Dirk Colbry
ICPR
2006
IEEE
16 years 26 days ago
Physics-based Fusion of Multispectral Data for Improved Face Recognition
A novel physics-based fusion of multispectral images within the visual spectra is proposed for the purpose of improving face recognition under constant or varying illumination. Sp...
Andreas Koschan, Besma R. Abidi, Hong Chang, Mongi...