Image Representation Using 2D Gabor Wavelets
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 by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
The Global Dimensionality of Face Space
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Information fusion in biometrics
Pattern Recognition Letters - Special issue: Audio- and video-based biometric person authentication (AVBPA 2001)
Optimal sampling of Gabor features for face recognition
Pattern Recognition Letters
Gabor-Based Kernel PCA with Fractional Power Polynomial Models for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature-Level Fusion in Personal Identification
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Local Linear Regression (LLR) for Pose Invariant Face Recognition
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improvements on CCA model with application to face recognition
Intelligent information processing II
Face Recognition Using Most Discriminative Local and Global Features
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Palmprint identification using feature-level fusion
Pattern Recognition
Locality preserving CCA with applications to data visualization and pose estimation
Image and Vision Computing
Gabor wavelets and General Discriminant Analysis for face identification and verification
Image and Vision Computing
Gabor wavelets and General Discriminant Analysis for face identification and verification
Image and Vision Computing
Journal of Cognitive Neuroscience
Face Recognition Using Multi-Resolution Transform
ICCIMA '07 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) - Volume 02
2D Gaborface representation method for face recognition with ensemble and multichannel model
Image and Vision Computing
Multiple feature fusion by subspace learning
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Multiresolution face recognition
Image and Vision Computing
A new method of feature fusion and its application in image recognition
Pattern Recognition
Face recognition based on generalized canonical correlation analysis
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
A shape- and texture-based enhanced Fisher classifier for face recognition
IEEE Transactions on Image Processing
Multiset canonical correlations analysis and multispectral, truly multitemporal remote sensing data
IEEE Transactions on Image Processing
Invariance properties of Gabor filter-based features-overview and applications
IEEE Transactions on Image Processing
Gabor-based kernel PCA with doubly nonlinear mapping for face recognition with a single face image
IEEE Transactions on Image Processing
Independent component analysis of Gabor features for face recognition
IEEE Transactions on Neural Networks
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For face recognition, image features are first extracted and then matched to those features in a gallery set. The amount of information and the effectiveness of the features used will determine the recognition performance. In this paper, we propose a novel face recognition approach using information about face images at higher and lower resolutions so as to enhance the information content of the features that are extracted and combined at different resolutions. As the features from different resolutions should closely correlate with each other, we employ the cascaded generalized canonical correlation analysis (GCCA) to fuse the information to form a single feature vector for face recognition. To improve the performance and efficiency, we also employ ''Gabor-feature hallucination'', which predicts the high-resolution (HR) Gabor features from the Gabor features of a face image directly by local linear regression. We also extend the algorithm to low-resolution (LR) face recognition, in which the medium-resolution (MR) and HR Gabor features of a LR input image are estimated directly. The LR Gabor features and the predicted MR and HR Gabor features are then fused using GCCA for LR face recognition. Our algorithm can avoid having to perform the interpolation/super-resolution of face images and having to extract HR Gabor features. Experimental results show that the proposed methods have a superior recognition rate and are more efficient than traditional methods.