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Face Recognition Algorithms surpass humans matching faces across changes in illumination



P. Jonathon Phillips, Alice J. O'Toole, Fang Jian, Julianne Ayadd, Nils Penard, Herve Abdi


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.


face recognition, human performance, computer performance


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 May 29, 2024)


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Created May 14, 2007, Updated February 19, 2017