Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Reflectance based object recognition
International Journal of Computer Vision
Face Recognition: The Problem of Compensating for Changes in Illumination Direction
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D and Infrared Face Reconstruction from RGB data using Canonical Correlation Analysis
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Illumination Invariant Face Recognition Using Near-Infrared Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Face recognition based on PCA/KPCA plus CCA
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Face recognition based on generalized canonical correlation analysis
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
Heterogeneous Face Recognition from Local Structures of Normalized Appearance
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
An Analysis-by-Synthesis Method for Heterogeneous Face Biometrics
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Partial Face Matching between Near Infrared and Visual Images in MBGC Portal Challenge
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
A super-resolution based method to synthesize visual images from near infrared
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A regularized correntropy framework for robust pattern recognition
Neural Computation
Face recognition using two-dimensional CCA and PLS
International Journal of Biometrics
Nighttime face recognition at long distance: cross-distance and cross-spectral matching
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Multi-feature canonical correlation analysis for face photo-sketch image retrieval
Proceedings of the 21st ACM international conference on Multimedia
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In many applications, such as E-Passport and driver's license, the enrollment of face templates is done using visible light (VIS) face images. Such images are normally acquired in controlled environment where the lighting is approximately frontal. However, Authentication is done in variable lighting conditions. Matching of faces in VIS images taken in different lighting conditions is still a big challenge. A recent development in near infrared (NIR) image based face recognition [1] has well overcome the difficulty arising from lighting changes. However, it requires that enrollment face images be acquired using NIR as well. In this paper, we present a new problem, that of matching a face in an NIR image against one in a VIS images, and propose a solution to it. The work is aimed to develop a new solution for meeting the accuracy requirement of face-based biometric recognition, by taking advantages of the recent NIR face technology while allowing the use of existing VIS face photos as gallery templates. Face recognition is done by matching an NIR probe face against a VIS gallery face. Based on an analysis of properties of NIR and VIS face images, we propose a learning-based approach for the different modality matching. A mechanism of correlation between NIR and VIS faces is learned from NIR → VIS face pairs, and the learned correlation is used to evaluate similarity between an NIR face and a VIS face. We provide preliminary results of NIR → VIS face matching for recognition under different illumination conditions. The results demonstrate advantages of NIR → VIS matching over VIS → VIS matching.