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Using Discriminant Eigenfeatures for Image Retrieval
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
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Laplacianfaces
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
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Kernel class-wise locality preserving projection
Information Sciences: an International Journal
IEEE Transactions on Pattern Analysis and Machine Intelligence
General Averaged Divergence Analysis
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Discriminative Locality Alignment
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Geometric Mean for Subspace Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature extraction based on Laplacian bidirectional maximum margin criterion
Pattern Recognition
Patch Alignment for Dimensionality Reduction
IEEE Transactions on Knowledge and Data Engineering
Transfer Discriminative Logmaps
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Bregman Divergence-Based Regularization for Transfer Subspace Learning
IEEE Transactions on Knowledge and Data Engineering
Directional binary code with application to PolyU near-infrared face database
Pattern Recognition Letters
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
On the Dimensionality Reduction for Sparse Representation Based Face Recognition
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Studies on hyperspectral face recognition in visible spectrum with feature band selection
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Max-Min Distance Analysis by Using Sequential SDP Relaxation for Dimension Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
A multi-manifold discriminant analysis method for image feature extraction
Pattern Recognition
Manifold elastic net: a unified framework for sparse dimension reduction
Data Mining and Knowledge Discovery
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
Manifold Regularized Discriminative Nonnegative Matrix Factorization With Fast Gradient Descent
IEEE Transactions on Image Processing
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UDP has been successfully applied in many fields, finding a subspace that maximizes the ratio of the nonlocal scatter to the local scatter. But UDP can not represent the nonlinear space well because it is a linear method in nature. Kernel methods can otherwise discover the nonlinear structure of the images. To improve the performance of UDP, kernel UDP (a nonlinear vision of UDP) is proposed for face feature extraction and face recognition via kernel tricks in this paper. We formulate the kernel UDP theory and develop a two-stage method to extract kernel UDP features: namely weighted Kernel PCA plus UDP. The experimental results on the FERET and ORL databases show that the proposed kernel UDP is effective.