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ICCV
2001
IEEE
14 years 7 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
ICCV
2007
IEEE
13 years 12 months ago
Support Kernel Machines for Object Recognition
Kernel classifiers based on Support Vector Machines (SVM) have recently achieved state-of-the art results on several popular datasets like Caltech or Pascal. This was possible by...
Ankita Kumar, Cristian Sminchisescu
ICCV
2003
IEEE
14 years 7 months ago
Recognition with Local Features: the Kernel Recipe
Recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. Support Vector Machines have be...
Christian Wallraven, Barbara Caputo, Arnulf B. A. ...
ICIP
2005
IEEE
14 years 7 months ago
Robust facial expression recognition using local binary patterns
A novel low-computation discriminative feature space is introduced for facial expression recognition capable of robust performance over a rang of image resolutions. Our approach i...
Caifeng Shan, Shaogang Gong, Peter W. McOwan
CVPR
2005
IEEE
13 years 11 months ago
Nonlinear Face Recognition Based on Maximum Average Margin Criterion
This paper proposes a novel nonlinear discriminant analysis method named by Kernerlized Maximum Average Margin Criterion (KMAMC), which has combined the idea of Support Vector Mac...
Baochang Zhang, Xilin Chen, Shiguang Shan, Wen Gao