TY - GEN
T1 - A meta-analysis of face recognition covariates
AU - Lui, Yui Man
AU - Bolme, David
AU - Draper, Bruce A.
AU - Beveridge, J. Ross
AU - Givens, Geoff
AU - Phillips, P. Jonathon
PY - 2009
Y1 - 2009
N2 - This paper presents a meta-analysis for covariates that affect performance of face recognition algorithms. Our review of the literature found six covariates for which multiple studies reported effects on face recognition performance. These are: age of the person, elapsed time between images, gender of the person, the person's expression, the resolution of the face images, and the race of the person. The results presented are drawn from 25 studies conducted over the past 12 years. There is near complete agreement between all of the studies that older people are easier to recognize than younger people, and recognition performance begins to degrade when images are taken more than a year apart. While individual studies find men or women easier to recognize, there is no consistent gender effect. There is universal agreement that changing expression hurts recognition performance. If forced to compare different expressions, there is still insufficient evidence to conclude that any particular expression is better than another. Higher resolution images improve performance for many modern algorithms. Finally, given the studies summarized here, no clear conclusions can be drawn about whether one racial group is harder or easier to recognize than another.
AB - This paper presents a meta-analysis for covariates that affect performance of face recognition algorithms. Our review of the literature found six covariates for which multiple studies reported effects on face recognition performance. These are: age of the person, elapsed time between images, gender of the person, the person's expression, the resolution of the face images, and the race of the person. The results presented are drawn from 25 studies conducted over the past 12 years. There is near complete agreement between all of the studies that older people are easier to recognize than younger people, and recognition performance begins to degrade when images are taken more than a year apart. While individual studies find men or women easier to recognize, there is no consistent gender effect. There is universal agreement that changing expression hurts recognition performance. If forced to compare different expressions, there is still insufficient evidence to conclude that any particular expression is better than another. Higher resolution images improve performance for many modern algorithms. Finally, given the studies summarized here, no clear conclusions can be drawn about whether one racial group is harder or easier to recognize than another.
UR - http://www.scopus.com/inward/record.url?scp=71749099594&partnerID=8YFLogxK
U2 - 10.1109/BTAS.2009.5339025
DO - 10.1109/BTAS.2009.5339025
M3 - Conference contribution
AN - SCOPUS:71749099594
SN - 9781424450206
T3 - IEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009
BT - IEEE 3rd International Conference on Biometrics
T2 - IEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009
Y2 - 28 September 2009 through 30 September 2009
ER -