Image-based Skin Analysis

Quantitative characterization of skin appearance is an important but difficult task. The skin surface is a detailed landscape, with features that depend on many variables such as body location (knuckle vs. torso), subject parameters (age/gender/health) and imaging parameters (lighting and camera). Computational modeling of skin texture has potential uses in many fields and 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 product comparison for cosmetics. In this work, image-based representations of skin appearance are used in order to have descriptive capabilities without the need for prohibitively complex physics-based skin models. We present a method for representing and recognizing different areas of the skin surface that have visibly different texture properties. Our model takes into account the varied appearance of the skin with changes in illumination and viewing directions.