Phillips, P.
, O'Toole, A.
, Jian, F.
, Ayadd, J.
, Penard, N.
and Abdi, H.
(2007),
Face Recognition Algorithms surpass humans matching faces across changes in illumination, Science
(Accessed October 2, 2025)
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.
Face Recognition Algorithms surpass humans matching faces across changes in illumination
Published
Author(s)
, Alice J. O'Toole, Fang Jian, Julianne Ayadd, Nils Penard, Herve Abdi
Abstract
We compared the accuracy of eight state-of-the-art face recognition algorithms with human performance on the same task. Humans and algorithms determined whether two face images, taken under different illumination conditions, were pictures of the same person or of different people. Three algorithms outperformed humans matching face pairs prescreened to be difficult and all but one algorithm was more accurate than humans on the easy face pairs. Although illumination variation continues to challenge face recognition algorithms, our results show that face recognition algorithms compete favorably with humans even with the popular perception that algorithms performed poorly in absolute terms.Citation
Science
Pub Type
Journals
Keywords
face recognition, human performance, computer performance
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact [email protected].
Created May 14, 2007, Updated February 19, 2017