Face recognition: the problem of compensating for changes in illumination direction
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
On Photometric Issues in 3D Visual Recognition from aSingle 2D Image
International Journal of Computer Vision
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: The Problem of Compensating for Changes in Illumination Direction
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations
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
An efficient representation for irradiance environment maps
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
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CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Illumination Normalization for Robust Face Recognition Against Varying Lighting Conditions
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Journal of Cognitive Neuroscience
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This paper considers the problem of recognizing faces under varying illuminations First, we investigate the statistics of the derivative of the irradiance images (log) of human face and find that the distribution is very sparse Based on this observation, we propose an illumination insensitive distance measure based on the min operator of the derivatives of two images Our experiments on the CMU-PIE database have shown that the proposed method improves the performance of a face recognition system when the probes are collected under varying lighting conditions.