Feature detection from local energy
Pattern Recognition Letters
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
Kernel Eigenfaces vs. Kernel Fisherfaces: Face Recognition Using Kernel Methods
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Robust Real-Time Face Detection
International Journal of Computer Vision
An improved face recognition technique based on modular PCA approach
Pattern Recognition Letters
Recognition of Expression Variant Faces Using Weighted Subspaces
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
IR and visible light face recognition
Computer Vision and Image Understanding
A Local Region-based Approach to Gender Classi.cation From Face Images
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Face Verification Using GaborWavelets and AdaBoost
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Journal of Cognitive Neuroscience
Thermal face recognition in an operational scenario
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Gabor feature based face recognition using kernel methods
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Kernel subspace LDA with optimized kernel parameters on face recognition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
An adaptive weight assignment scheme in linear subspace approaches for face recognition
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Phase space for face pose estimation
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
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A feature selection technique along with an information fusion procedure for improving the recognition accuracy of a visual and thermal image-based facial recognition system is presented in this paper. A novel modular kernel eigenspaces approach is developed and implemented on the phase congruency feature maps extracted from the visual and thermal images individually. Smaller sub-regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are then projected into higher dimensional spaces using kernel methods. The proposed localized nonlinear feature selection procedure helps to overcome the bottlenecks of illumination variations, partial occlusions, expression variations and variations due to temperature changes that affect the visual and thermal face recognition techniques. AR and Equinox databases are used for experimentation and evaluation of the proposed technique. The proposed feature selection procedure has greatly improved the recognition accuracy for both the visual and thermal images when compared to conventional techniques. Also, a decision level fusion methodology is presented which along with the feature selection procedure has outperformed various other face recognition techniques in terms of recognition accuracy.