Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

A Meta-Analysis of Face Recognition Covariates



Yui M. Lui, David Bolme, Bruce A. Draper, J. R. Beveridge, Geof H. Givens, P. Jonathon Phillips


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
Proceedings Title
Biometrics: Theory, Applications and Systems (BTAS 09)
Conference Dates
September 28-30, 2009
Conference Location
Crystal City, VA, US


Lui, Y. , Bolme, D. , Draper, B. , Beveridge, J. , Givens, G. and Phillips, P. (2010), A Meta-Analysis of Face Recognition Covariates, Biometrics: Theory, Applications and Systems (BTAS 09), Crystal City, VA, US, [online], (Accessed April 18, 2024)
Created November 21, 2010, Updated October 12, 2021