The CHROMA-FIT Dataset: Characterizing Human Ranges of Melanin For Increased Tone-awareness.

The disparate performance of face analytics technology across demographic groups is a well-documented phe-nomenon. In particular, these systems tend toward lower accuracy for darker-skinned individuals. Prior research ex-ploring this asymmetry has largely relied on discrete race categories, but such labels are increasingly deemed insuf-ficient to describe the wide range of human phenotypical features. Skin tone is a more objective measure, but there is a dearth of reliable skin tone-related image data. Ex-isting tone annotations are derived from the images alone, either by human reviewers or automated processes. However, without ground-truth skin tone measurements from the subjects of the images themselves, there is no way to as-sess the consistency or accuracy of post-hoc methods. In this work, we present CHROMA-FIT, the first publicly available dataset of face images and corresponding ground-truth skin tone measurements. Our goal is to provide a baseline for tone-labeling methods in assessing and improving their accuracy. The dataset comprises approximately 2,300 still images of 209 participants in indoor and outdoor collection environments.