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FGR
2011
IEEE
255views Biometrics» more  FGR 2011»
13 years 23 days ago
Beyond simple features: A large-scale feature search approach to unconstrained face recognition
— Many modern computer vision algorithms are built atop of a set of low-level feature operators (such as SIFT [1], [2]; HOG [3], [4]; or LBP [5], [6]) that transform raw pixel va...
David D. Cox, Nicolas Pinto
ICCV
2001
IEEE
14 years 11 months ago
Face Recognition with Support Vector Machines: Global versus Component-based Approach
We present a component-based method and two global methods for face recognition and evaluate them with respect to robustness against pose changes. In the component system we first...
Bernd Heisele, Purdy Ho, Tomaso Poggio
FGR
2000
IEEE
150views Biometrics» more  FGR 2000»
14 years 1 months ago
From Few to Many: Generative Models for Recognition Under Variable Pose and Illumination
Image variability due to changes in pose and illumination can seriously impair object recognition. This paper presents appearance-based methods which, unlike previous appearance-b...
Athinodoros S. Georghiades, Peter N. Belhumeur, Da...
AVBPA
2001
Springer
145views Biometrics» more  AVBPA 2001»
14 years 1 months ago
Using Mixture Covariance Matrices to Improve Face and Facial Expression Recognitions
In several pattern recognition problems, particularly in image recognition ones, there are often a large number of features available, but the number of training samples for each p...
Carlos E. Thomaz, Duncan Fyfe Gillies, Raul Queiro...
TIP
2011
137views more  TIP 2011»
13 years 3 months ago
Boosting Color Feature Selection for Color Face Recognition
—This paper introduces the new color face recognition (FR) method that makes effective use of boosting learning as color-component feature selection framework. The proposed boost...
Jae Young Choi, Yong Man Ro, Konstantinos N. Plata...