Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wavelets for Computer Graphics: A Primer, Part 1
IEEE Computer Graphics and Applications
Discriminant Waveletfaces and Nearest Feature Classifiers for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
A GENERIC FACE REPRESENTATION APPROACH FOR LOCAL APPEARANCE BASED FACE VERIFICATION
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Total Variation Models for Variable Lighting Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multiscale and Multidirectional Image Denoising Algorithm Based on Contourlet Transform
IIH-MSP '06 Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia
Journal of Cognitive Neuroscience
Face Recognition Based on Wavelet Transform Weighted Modular PCA
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04
Contourlet-Based Feature Extraction with PCA for Face Recognition
AHS '08 Proceedings of the 2008 NASA/ESA Conference on Adaptive Hardware and Systems
Curvelet based face recognition via dimension reduction
Signal Processing
Binary sparse nonnegative matrix factorization
IEEE Transactions on Circuits and Systems for Video Technology
Iterative subspace analysis based on feature line distance
IEEE Transactions on Image Processing
Steerable pyramid-based face hallucination
Pattern Recognition
Comparison and fusion of multiresolution features for texture classification
Pattern Recognition Letters
An image preprocessing algorithm for illumination invariant face recognition
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Enhanced local texture feature sets for face recognition under difficult lighting conditions
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Novel face recognition approach based on steerable pyramid feature extraction
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Effective Feature Extraction in High-Dimensional Space
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Rotation-invariant texture retrieval with gaussianized steerable pyramids
IEEE Transactions on Image Processing
Face recognition by applying wavelet subband representation and kernel associative memory
IEEE Transactions on Neural Networks
Face recognition by curvelet based feature extraction
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Block-based Deep Belief Networks for face recognition
International Journal of Biometrics
Score fusion in multibiometric identification based on fuzzy set theory
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
Hierarchical Correlation of Multi-Scale Spatial Pyramid for Similar Mammogram Retrieval
International Journal of Digital Library Systems
Multiple kernel local Fisher discriminant analysis for face recognition
Signal Processing
Learning colours from textures by sparse manifold embedding
Signal Processing
Pose invariant face recognition using biological inspired features based on ensemble of classifiers
Journal of Visual Communication and Image Representation
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In this paper, an efficient local appearance feature extraction method based on Steerable Pyramid (S-P) wavelet transform is proposed for face recognition. Local information is extracted by computing the statistics of each sub-block obtained by dividing S-P sub-bands. The obtained local features of each sub-band are combined at the feature and decision level to enhance face recognition performance. The purpose of this paper is to explore the usefulness of S-P as feature extraction method for face recognition. The proposed approach is compared with some related feature extraction methods such as principal component analysis (PCA), as well as linear discriminant analysis LDA and boosted LDA. Different multi-resolution transforms, wavelet (DWT), gabor, curvelet and contourlet, are also compared against the block-based S-P method. Experimental results on ORL, Yale, Essex and FERET face databases convince us that the proposed method provides a better representation of the class information, and obtains much higher recognition accuracies in real-world situations including changes in pose, expression and illumination.