From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition with one training image per person
Pattern Recognition Letters
The CMU Pose, Illumination, and Expression (PIE) Database
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Enhanced (PC)2 A for face recognition with one training image per person
Pattern Recognition Letters
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Total Variation Models for Variable Lighting Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition from a single image per person: A survey
Pattern Recognition
Enhancing Bilinear Subspace Learning by Element Rearrangement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Semi-supervised bilinear subspace learning
IEEE Transactions on Image Processing
Face recognition under varying illumination using gradientfaces
IEEE Transactions on Image Processing
Selecting discriminant eigenfaces for face recognition
Pattern Recognition Letters
Authenticating corrupted face image based on noise model
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Face recognition under varying lighting conditions using self quotient image
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Face recognition under variable lighting using harmonic image exemplars
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Rank-One Projections With Adaptive Margins for Face Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A multiscale retinex for bridging the gap between color images and the human observation of scenes
IEEE Transactions on Image Processing
Reconstruction and Recognition of Tensor-Based Objects With Concurrent Subspaces Analysis
IEEE Transactions on Circuits and Systems for Video Technology
Convergent 2-D Subspace Learning With Null Space Analysis
IEEE Transactions on Circuits and Systems for Video Technology
Face and Human Gait Recognition Using Image-to-Class Distance
IEEE Transactions on Circuits and Systems for Video Technology
Face recognition with enhanced local directional patterns
Neurocomputing
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Due to the limitation of the storage space in the real-world face recognition application systems, only one sample image per person is often stored in the system, which is the so-called single sample problem. Moreover, real-world illumination has impact on recognition performance. This paper presents an illumination robust single sample face recognition approach, which utilizes multi-directional orthogonal gradient phase faces to solve the above limitations. In the proposed approach, an illumination insensitive orthogonal gradient phase face is obtained by using two vertical directional gradient values of the original image. Multi-directional orthogonal gradient phase faces can be used to extend samples for single sample face recognition. Simulated experiments and comparisons on a subset of Yale B database, Yale database, a subset of PIE database and VALID face database show that the proposed approach is not only an outstanding method for single sample face recognition under illumination but also more effective when addressing illumination, expression, decoration, etc.