  We explore varying face recognition accuracy across demographic groups as a
phenomenon partly caused by differences in face illumination. We observe that
for a common operational scenario with controlled image acquisition, there is a
large difference in face region brightness between African-American and
Caucasian, and also a smaller difference between male and female. We show that
impostor image pairs with both faces under-exposed, or both overexposed, have
an increased false match rate (FMR). Conversely, image pairs with strongly
different face brightness have a decreased similarity measure. We propose a
brightness information metric to measure variation in brightness in the face
and show that face brightness that is too low or too high has reduced
information in the face region, providing a cause for the lower accuracy. Based
on this, for operational scenarios with controlled image acquisition,
illumination should be adjusted for each individual to obtain appropriate face
image brightness. This is the first work that we are aware of to explore how
the level of brightness of the skin region in a pair of face images (rather
than a single image) impacts face recognition accuracy, and to evaluate this as
a systematic factor causing unequal accuracy across demographics. The code is
at https://github.com/HaiyuWu/FaceBrightness.
