Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Lambertian Reflectance and Linear Subspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Based on Nearest Linear Combinations
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Acquiring Linear Subspaces for Face Recognition under Variable Lighting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Discriminant Embedding and Its Variants
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A review on Gabor wavelets for face recognition
Pattern Analysis & Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved face representation by nonuniform multilevel selection of Gabor convolution features
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image and Vision Computing
Kernel sparse representation for image classification and face recognition
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Gabor feature based sparse representation for face recognition with gabor occlusion dictionary
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Linear Regression for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning a discriminative dictionary for sparse coding via label consistent K-SVD
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Robust sparse coding for face recognition
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Robust classification using structured sparse representation
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
IEEE Transactions on Image Processing
Face recognition using the nearest feature line method
IEEE Transactions on Neural Networks
Combining Perceptual Features With Diffusion Distance for Face Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Passive Multimodal 2-D+3-D Face Recognition Using Gabor Features and Landmark Distances
IEEE Transactions on Information Forensics and Security
Fisher Discrimination Dictionary Learning for sparse representation
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Sparse representation or collaborative representation: Which helps face recognition?
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Robust face recognition via occlusion dictionary learning
Pattern Recognition
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By representing the input testing image as a sparse linear combination of the training samples via l"1-norm minimization, sparse representation based classification (SRC) has shown promising results for face recognition (FR). Particularly, by introducing an identity occlusion dictionary to code the occluded portions of face images, SRC could lead to robust FR results against face occlusion. However, the l"1-norm minimization and the high number of atoms in the identity occlusion dictionary make the SRC scheme computationally very expensive. In this paper, a Gabor feature based robust representation and classification (GRRC) scheme is proposed for robust FR. The use of Gabor features not only increases the discrimination power of face representation, but also allows us to compute a compact Gabor occlusion dictionary which has much less atoms than the identity occlusion dictionary. Furthermore, we show that with Gabor feature transformation, l"2-norm could take the role of l"1-norm to regularize the coding coefficients, which reduces significantly the computational cost in coding occluded face images. Our extensive experiments on benchmark face databases, which have variations of lighting, expression, pose and occlusion, demonstrated the high effectiveness and efficiency of the proposed GRRC method.