Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
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
Lambertian Reflectance and Linear Subspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
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
Hierarchical ensemble of global and local classifiers for face recognition
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Feature Extraction Using Laplacian Maximum Margin Criterion
Neural Processing Letters
Face Recognition Using Kernel UDP
Neural Processing Letters
Retrieval-based face annotation by weak label regularized local coordinate coding
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Robust visual tracking with structured sparse representation appearance model
Pattern Recognition
Sparse Representation Classifier for microaneurysm detection and retinal blood vessel extraction
Information Sciences: an International Journal
Heteroscedastic Sparse Representation Based Classification for Face Recognition
Neural Processing Letters
Identification of great apes using gabor features and locality preserving projections
Proceedings of the 1st ACM international workshop on Multimedia analysis for ecological data
Collaborative neighbor representation based classification using l2-minimization approach
Pattern Recognition Letters
V1-Inspired features induce a weighted margin in SVMs
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Sparse coding and dictionary learning for symmetric positive definite matrices: a kernel approach
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
An automated methodology for assessing the damage on byzantine icons
EuroMed'12 Proceedings of the 4th international conference on Progress in Cultural Heritage Preservation
Sparse coding based visual tracking: Review and experimental comparison
Pattern Recognition
Discriminative dictionary learning with pairwise constraints
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Letters: Two-dimensional relaxed representation
Neurocomputing
Face recognition for web-scale datasets
Computer Vision and Image Understanding
Robust face recognition via occlusion dictionary learning
Pattern Recognition
Bilinear discriminative dictionary learning for face recognition
Pattern Recognition
Hi-index | 0.00 |
By coding the input testing image as a sparse linear combination of the training samples via l1-norm minimization, sparse representation based classification (SRC) has been recently successfully used for face recognition (FR). Particularly, by introducing an identity occlusion dictionary to sparsely code the occluded portions in face images, SRC can lead to robust FR results against occlusion. However, the large amount of atoms in the occlusion dictionary makes the sparse coding computationally very expensive. In this paper, the image Gabor-features are used for SRC. The use of Gabor kernels makes the occlusion dictionary compressible, and a Gabor occlusion dictionary computing algorithm is then presented. The number of atoms is significantly reduced in the computed Gabor occlusion dictionary, which greatly reduces the computational cost in coding the occluded face images while improving greatly the SRC accuracy. Experiments on representative face databases with variations of lighting, expression, pose and occlusion demonstrated the effectiveness of the proposed Gabor-feature based SRC (GSRC) scheme.