Quantitative characterization of skin appearance is an important but difficult
task. The skin surface is a detailed landscape, with complex geometry and
local optical properties. In addition, skin features depend on many variables
such as body location (e.g. forehead, cheek), subject parameters (age, gender)
and imaging parameters (lighting, camera). As with many real world surfaces,
skin appearance is strongly affected by the direction from which it is viewed
and illuminated. Computational modeling of skin texture has potential uses in
many applications including realistic rendering for computer graphics, robust
face models for computer vision, computer-assisted diagnosis for dermatology,
topical drug efficacy testing for the pharmaceutical industry and quantitative
comparison for consumer products. In this work we present models and
measurements of skin texture with an emphasis on faces. We develop two models
for use in skin texture recognition. Both models are image-based
representations of skin appearance that are suitably descriptive without the
need for prohibitively complex physics-based skin models. Our models take into
account the varied appearance of the skin with changes in illumination and
viewing direction. We also present a new face texture database comprised of
more than 2400 images corresponding to 20 human faces, 4 locations on each face
(forehead, cheek, chin and nose) and 32 combinations of imaging angles. The
complete database is made publicly available for further research.
International Journal of Computer Vision, Vol. 62: No. 1-2, pp. 97-119, April-May 2005 (submitted November 2002, submitted revised April 2003, submitted camera-ready June 2003).
This material is based upon work supported by the National Science Foundation under Grant No. 0092491 and Grant No. 0085864.