Quantifying How Lighting and Focus Affect Face Recognition Performance
J. R. Beveridge, David Bolme, Bruce A. Draper, Geof H. Givens, Yui M. Lui, P. Jonathon Phillips
Recent studies show that face recognition in uncontrolled images remains a challenging problem, although the reasons why are less clear. Changes in illumination are one possible explanation, although algorithms developed since the advent of the PIE and Yale B data bases supposedly compensate for illumination variation. Edge density has also been shown to be a strong predictor of algorithm failure on the FRVT 2006 uncontrolled images: recognition is harder on images with higher edge density. This paper presents a new study that explains the edge density effect in terms of illumination and shows that top performing algorithms in FRVT 2006 are still sensitive to lighting. This new study also shows that focus, originally suggested as an explanation for the edge density effect, is not a significant factor. The new lighting model developed in this study can be used as a measure of face image quality.
IEEE Conference on Computer Vision and Pattern Recognition
, Bolme, D.
, Draper, B.
, Givens, G.
, Lui, Y.
and Phillips, P.
Quantifying How Lighting and Focus Affect Face Recognition Performance, IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, US
(Accessed February 22, 2024)