Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
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
Face Recognition: The Problem of Compensating for Changes in Illumination Direction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representation and recognition in vision
Representation and recognition in vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiclass Linear Dimension Reduction by Weighted Pairwise Fisher Criteria
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robot Vision
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
The CMU Pose, Illumination, and Expression Database
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal sampling of Gabor features for face recognition
Pattern Recognition Letters
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
The Journal of Machine Learning Research
Subclass Discriminant Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Weighted Sub-Gabor for face recognition
Pattern Recognition Letters
Simplified Gabor wavelets for human face recognition
Pattern Recognition
Journal of Cognitive Neuroscience
Eigenfeature Regularization and Extraction in Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Orthogonal neighborhood preserving discriminant analysis for face recognition
Pattern Recognition
Facial feature extraction using complex dual-tree wavelet transform
Computer Vision and Image Understanding
Asymmetric Principal Component and Discriminant Analyses for Pattern Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Photometric normalisation for face verification
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Generalizing discriminant analysis using the generalized singular value decomposition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust coding schemes for indexing and retrieval from large face databases
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Information Sciences: an International Journal
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This paper presents a novel face recognition method which integrates the Augmented Dual-Tree Complex Wavelet Transform (ADT-CWT) representation of face images and Regularized Neighborhood Projection Discriminant Analysis (RNPDA) method. ADT-CWT first derives desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. Different from DT-CWT, which does not consider the structural characteristics of the face images, our representation method not only considers the statistical property of the input features but also adopts an Eigenmask to emphasize those important facial feature points. The dimensionality of the derivation of ADT-CWT feature is further reduced by using RNPDA, which directly obtain a set of optimal eigenvectors with a simple regression framework and thus can overcome the small sample size problem of NPDA. Extensive experiments have been made to compare the recognition performance of the proposed method with some popular dimensionality reduction methods on the FERET database, the extended YALEB database and the CMU PIE database. The results verify the effectiveness of the proposed method.