Direct sparse nearest feature classifier for face recognition
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
A regularized correntropy framework for robust pattern recognition
Neural Computation
Robust regression for face recognition
Pattern Recognition
Robust classification using l2,1-norm based regression model
Pattern Recognition
Spatial feature interdependence matrix (SFIM): a robust descriptor for face recognition
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part I
A new subspace approach for face recognition
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
Live sharing with multimodal modes in mobile network
Journal of Mobile Multimedia
Component-based global k-NN classifier for small sample size problems
Pattern Recognition Letters
Weighted group sparse representation based on robust regression for face recognition
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
K-local hyperplane distance nearest neighbor classifier oriented local discriminant analysis
Information Sciences: an International Journal
Measuring the degree of face familiarity based on extended NMF
ACM Transactions on Applied Perception (TAP)
Statistical framework for facial pose classification
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Pattern Recognition Letters
Classification approach based on non-negative least squares
Neurocomputing
Feature Extraction Based on Maximum Nearest Subspace Margin Criterion
Neural Processing Letters
Face recognition for web-scale datasets
Computer Vision and Image Understanding
Linear reconstruction measure steered nearest neighbor classification framework
Pattern Recognition
Least squares estimation-based adaptive observation model for aerial visual tracking applications
International Journal of Computational Vision and Robotics
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In this paper, we present a novel approach of face identification by formulating the pattern recognition problem in terms of linear regression. Using a fundamental concept that patterns from a single-object class lie on a linear subspace, we develop a linear model representing a probe image as a linear combination of class-specific galleries. The inverse problem is solved using the least-squares method and the decision is ruled in favor of the class with the minimum reconstruction error. The proposed Linear Regression Classification (LRC) algorithm falls in the category of nearest subspace classification. The algorithm is extensively evaluated on several standard databases under a number of exemplary evaluation protocols reported in the face recognition literature. A comparative study with state-of-the-art algorithms clearly reflects the efficacy of the proposed approach. For the problem of contiguous occlusion, we propose a Modular LRC approach, introducing a novel Distance-based Evidence Fusion (DEF) algorithm. The proposed methodology achieves the best results ever reported for the challenging problem of scarf occlusion.