IEEE Transactions on Pattern Analysis and Machine Intelligence
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems
Theoretical Computer Science
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Atomic Decomposition by Basis Pursuit
SIAM Review
Discriminant Waveletfaces and Nearest Feature Classifiers for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
The CMU Pose, Illumination, and Expression Database
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Generalized spectral bounds for sparse LDA
ICML '06 Proceedings of the 23rd international conference on Machine learning
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning a dictionary of shape-components in visual cortex: comparison with neurons, humans and machines
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sparsity preserving projections with applications to face recognition
Pattern Recognition
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Dense error correction via l1-minimization
IEEE Transactions on Information Theory
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Matching pursuits with time-frequency dictionaries
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
IEEE Transactions on Information Theory
Morphological Component Analysis: An Adaptive Thresholding Strategy
IEEE Transactions on Image Processing
Face recognition using the nearest feature line method
IEEE Transactions on Neural Networks
Face recognition using discriminant sparsity neighborhood preserving embedding
Knowledge-Based Systems
Linear reconstruction measure steered nearest neighbor classification framework
Pattern Recognition
Weighted discriminative sparsity preserving embedding for face recognition
Knowledge-Based Systems
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The newly-emerging sparse representation-based classifier (SRC) shows great potential for pattern classification but lacks theoretical justification. This paper gives an insight into SRC and seeks reasonable supports for its effectiveness. SRC uses L"1-optimizer instead of L"0-optimizer on account of computational convenience and efficiency. We re-examine the role of L"1-optimizer and find that for pattern recognition tasks, L"1-optimizer provides more classification meaningful information than L"0-optimizer does. L"0-optimizer can achieve sparsity only, whereas L"1-optimizer can achieve closeness as well as sparsity. Sparsity determines a small number of nonzero representation coefficients, while closeness makes the nonzero representation coefficients concentrate on the training samples with the same class label as the given test sample. Thus, it is closeness that guarantees the effectiveness of the L"1-optimizer based SRC. Based on the closeness prior, we further propose two kinds of class L"1-optimizer classifiers (CL"1C), the closeness rule based CL"1C (C-CL"1C) and its improved version: the Lasso rule based CL"1C (L-CL"1C). The proposed classifiers are evaluated on five databases and the experimental results demonstrate advantages of the proposed classifiers over SRC in classification performance and computational efficiency for large sample size problems.