From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Total Variation Models for Variable Lighting Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition under varying illumination using gradientfaces
IEEE Transactions on Image Processing
FRVT 2006 and ICE 2006 Large-Scale Experimental Results
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling visual perception for image processing
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Using Human Visual System modeling for bio-inspired low level image processing
Computer Vision and Image Understanding
Illumination-robust face recognition using retina modeling
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A multiscale retinex for bridging the gap between color images and the human observation of scenes
IEEE Transactions on Image Processing
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An effective illumination normalization method based on human visual system is presented for extreme lighting face recognition. One contribution is that illumination normalization based on retinal modeling is mainly executed on low frequency band considering lighting conditions, the other is the introduction of discrete wavelet transform into human visual modeling for illumination normalization. The proposed method not only gets better illumination normalized result, but also preserves more image details. Both of them are very important for face recognition under complex lighting conditions. Experimental results on extended Yale B face databases demonstrate that our method is effective for dealing with variable lighting, especially for extreme lighting variation situation.