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» Using Component Features for Face Recognition
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IWBRS
2005
Springer
168views Biometrics» more  IWBRS 2005»
14 years 1 months ago
Gabor Feature Selection for Face Recognition Using Improved AdaBoost Learning
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual infor...
LinLin Shen, Li Bai, Daniel Bardsley, Yangsheng Wa...
ICIP
2009
IEEE
14 years 8 months ago
Determining Discriminative Anatomical Point Pairings Using Adaboost For 3d Face Recognition
In this paper, we present a novel method for 3D face recognition using adaboosted geodesic distance features. Firstly, a generic model is finely conformed to each face model conta...
MVA
2007
191views Computer Vision» more  MVA 2007»
13 years 7 months ago
Face recognition using localized features based on non-negative sparse coding
Neural networks in the visual system may be performing sparse coding of learnt local features that are qualitatively
Bhavin J. Shastri, Martin D. Levine
CVPR
2006
IEEE
14 years 1 months ago
3D Face Recognition Using 3D Alignment for PCA
This paper presents a 3D approach for recognizing faces based on Principal Component Analysis (PCA). The approach addresses the issue of proper 3D face alignment required by PCA f...
Trina Russ, Chris Boehnen, Tanya Peters
PAMI
2006
333views more  PAMI 2006»
13 years 7 months ago
Face Description with Local Binary Patterns: Application to Face Recognition
This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from whi...
Timo Ahonen, Abdenour Hadid, Matti Pietikäine...