Face-based Luminance Matching for Perceptual Colormap Generation

Gordon Kindlmann Erik Reinhard Sarah Creem
School of Computing
University of Utah
School of Electrical Engineering and Computer Science
University of Central Florida
Department of Psychology
University of Utah


Most systems used for creating and displaying colormap-based visualizations are not photometrically calibrated. That is, the relationship between RGB input levels and perceived luminance is usually not known, due to variations in the monitor, hardware configuration, and the viewing environment. However, the luminance component of perceptually based colormaps should be controlled, due to the central role that luminance plays in our visual processing. We address this problem with a simple and effective method for performing luminance matching on an uncalibrated monitor. The method is akin to the minimally distinct border technique (a previous method of luminance matching used for measuring luminous efficiency), but our method relies on the brain's highly developed ability to distinguish human faces. We present a user study showing that our method produces equivalent results to the minimally distinct border technique, but with significantly improved precision. We demonstrate how results from our luminance matching method can be directly applied to create new univariate colormaps.

Normally I would think it better to read the paper than view an online version of the talk, but in this case I think the talk explains things more clearly than the paper does. If reading both, I suggest the ordering above.