Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Instance-Based Learning Algorithms
Machine Learning
Discriminant Adaptive Nearest Neighbor Classification
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
Toward Improved Ranking Metrics
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
Empirical Evaluation Techniques in Computer Vision
Empirical Evaluation Techniques in Computer Vision
Advances in Instance Selection for Instance-Based Learning Algorithms
Data Mining and Knowledge Discovery
Locally Adaptive Metric Nearest-Neighbor Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discriminant Waveletfaces and Nearest Feature Classifiers for Face Recognition
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)
The CMU Pose, Illumination, and Expression Database
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
Metric Learning for Text Documents
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nearest Neighbors by Neighborhood Counting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Weighted Metrics to Minimize Nearest-Neighbor Classification Error
IEEE Transactions on Pattern Analysis and Machine Intelligence
Prototype selection for dissimilarity-based classifiers
Pattern Recognition
Improving nearest neighbor rule with a simple adaptive distance measure
Pattern Recognition Letters
The Bayes Decision Rule Induced Similarity Measures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distributed Nearest Neighbor-Based Condensation of Very Large Data Sets
IEEE Transactions on Knowledge and Data Engineering
Fast Nearest Neighbor Condensation for Large Data Sets Classification
IEEE Transactions on Knowledge and Data Engineering
A memetic algorithm for evolutionary prototype selection: A scaling up approach
Pattern Recognition
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal on Imaging Sciences
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal on Imaging Sciences
Linear Regression for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selecting Critical Patterns Based on Local Geometrical and Statistical Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Beyond sparsity: The role of L1-optimizer in pattern classification
Pattern Recognition
Is face recognition really a Compressive Sensing problem?
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
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
Face recognition using the nearest feature line method
IEEE Transactions on Neural Networks
Sparse representation or collaborative representation: Which helps face recognition?
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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The linear reconstruction measure (LRM), which determines the nearest neighbors of the query sample in all known training samples by sorting the minimum L"2-norm error linear reconstruction coefficients, is introduced in this paper. The intuitive interpretation and mathematical proofs are presented to reveal the efficient working mechanism of LRM. Through analyzing the physical meaning of coefficients and regularization items, we find that LRM provides more useful information and advantages than the conventional similarity measure model which calculates the distance between two entities (i.e. conventional point-to-point, C-PtP). Inspired by the advantages of LRM, the linear reconstruction measure steered nearest neighbor classification framework (LRM-NNCF) is designed with eight classifiers according to different decision rules and models of LRM. Evaluation on several face databases and the experimental results demonstrate that these proposed classifiers can achieve greater performance than the C-PtP based 1-NNs and competitive recognition accuracy and robustness compared with the state-of-the-art classifiers.