TY - GEN
T1 - Quantifying how lighting and focus affect face recognition performance
AU - Beveridge, J. Ross
AU - Bolme, David S.
AU - Draper, Bruce A.
AU - Givens, Geof H.
AU - Lui, Yui Man
AU - Jonathon Phillips, P.
PY - 2010
Y1 - 2010
N2 - 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, even though 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.
AB - 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, even though 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.
UR - http://www.scopus.com/inward/record.url?scp=77956506277&partnerID=8YFLogxK
U2 - 10.1109/CVPRW.2010.5543228
DO - 10.1109/CVPRW.2010.5543228
M3 - Conference contribution
AN - SCOPUS:77956506277
SN - 9781424470297
T3 - 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
SP - 74
EP - 81
BT - 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
T2 - 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
Y2 - 13 June 2010 through 18 June 2010
ER -