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

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, as measured by d’ between distributions. To balance brightness across demographic groups, we conduct three experiments, interpreting brightness in the face skin region either as median pixel value or as the distribution of pixel values. Balancing based on median brightness alone yields up to a 46.8% decrease in d’, while balancing based on brightness distribution yields 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.

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Publication Details

Published
2025-02-28
DOI
https://doi.org/10.1109/wacvw65960.2025.00024
Citations
3
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
3.83
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article

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

Kevin W. Bowyer, Haiyu Wu, Gabriella Pangelinan, Grace Bezold et al.
3 citations
Face recognition and analysis
3.83
article

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

Kevin W. Bowyer, Haiyu Wu, Gabriella Pangelinan, Grace Bezold, Michael C. King
article en
3 citations

Abstract

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, as measured by d’ between distributions. To balance brightness across demographic groups, we conduct three experiments, interpreting brightness in the face skin region either as median pixel value or as the distribution of pixel values. Balancing based on median brightness alone yields up to a 46.8% decrease in d’, while balancing based on brightness distribution yields 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.

Florida Institute of Technology (US), University of Notre Dame (US)
Openalex Percentile: Top 7%
Face recognition and analysis
3.83
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Lights, Camera, Matching: The Role of Image Illumination in Fair Face Recognition — Kevin W. Bowyer, Haiyu Wu, et al. · (2025) | TGRS Research Map | TGRS