SREDS: A dichromatic separation based measure of skin color

Chinmay Sahu

Abstract:

Face recognition (FR) systems are fast becoming
ubiquitous. However, differential performance among certain
demographics was identified in several widely used FR models.
The skin tone of the subject is an important factor in addressing
the differential performance. Previous work has used modeling
methods to propose skin tone measures of subjects across
different illuminations or utilized subjective labels of skin color
and demographic information. However, such models heavily rely
on consistent background and lighting for calibration or utilize
labeled datasets, which are time-consuming to generate or are
unavailable. In this work, we have developed a novel and datadriven skin color measure capable of accurately representing
subjects’ skin tone from a single image, without requiring a
consistent background or illumination. Our measure leverages
the dichromatic reflection model in RGB space to decompose
skin patches into diffuse and specular bases.