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Weber's law suggests that for a stimulus, the ratio between the smallest perceptual change and the background is a constant, which implies stimuli are perceived not in absolute terms but in relative terms. Inspired from this, we exploit and analyze a novel illumination insensitive representation of face images under varying illuminations via a ratio image, called “Weber-face,” where a ratio between local intensity variation and the background is computed. Experimental results on both CMU-PIE and Yale B face databases show that Weber-face performs better than the existing representative approaches.
Date of Publication: Aug. 2011