Wassim Kabbani, Christoph BuschDamer, NaserGomez-Barrero, MartaRaja, KiranRathgeb, ChristianSequeira, Ana F.Todisco, MassimilianoUhl, Andreas2023-12-122023-12-122023978-3-88579-733-31617-5468https://dl.gi.de/handle/20.500.12116/43260Face image quality assessment (FIQA) is crucial for obtaining good face recognition performance. FIQA algorithms should be robust and insensitive to demographic factors. The eye sclera has a consistent whitish color in all humans regardless of their age, ethnicity and skin-tone. This work proposes a robust sclera segmentation method that is suitable for face images in the enrolment and the border control face recognition scenarios. It shows how the statistical analysis of the sclera pixels produces features that are invariant to skin-tone, age and ethnicity and thus can be incorporated into FIQA algorithms to make them agnostic to demographic factors.enFace and gesture recognitionBiometric sample quality; Ethicallegal and socio-technological aspects; Soft biometric privacyDemographic biasFairnessRobust Sclera Segmentation for Skin-tone Agnostic Face Image Quality AssessmentText/Conference Paper