Lights Camera Matching: The Role of Image Illumination in Fair Face Recognition

Gabriella Pangelinan, Grace Bezold, Haiyu Wu, Michael C King, Kevin W Bowyer; Proceedings of the Winter Conference on Applications of Computer Vision (WACV) Workshops, 2025, pp. 177-186

Facial brightness is a key image quality factor impacting face recognition accuracy differentials across demographic groups. In this work we aim to decrease the accuracy gap between the similarity score distributions for Caucasian and African American female mated image pairs (measured by d') with three methods controlling for brightness-based factors. We interpret face image brightness as it relates to either median brightness value for the face skin region or the distribution of brightness values across the face. Our method for balancing across race based on median brightness alone yields up to a 46.8% decrease in d' while the methods for balancing brightness distribution yield up to a 57.6% decrease. In all three cases the similarity scores of the individual distributions improve with mean scores maximally improving 5.9% for Caucasian females and 3.7% for African American females