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Face Recognition Algorithms Surpass Humans Matching Faces

Summary: Face Recognition Algorithms
Surpass Humans Matching Faces
over Changes in Illumination
Alice J. O'Toole,
P. Jonathon Phillips, Senior Member, IEEE,
Fang Jiang, Janet Ayyad, Nils Pe´nard,
and Herve´ Abdi
Abstract--There has been significant progress in improving the performance of
computer-based face recognition algorithms over the last decade. Although
algorithms have been tested and compared extensively with each other, there has
been remarkably little work comparing the accuracy of computer-based face
recognition systems with humans. We compared seven state-of-the-art face
recognition algorithms with humans on a face-matching task. Humans and
algorithms determined whether pairs of face images, taken under different
illumination conditions, were pictures of the same person or of different people.
Three algorithms surpassed human performance matching face pairs prescreened
to be "difficult" and six algorithms surpassed humans on "easy" face pairs. Although
illumination variation continues to challenge face recognition algorithms, current
algorithms compete favorably with humans. The superior performance of the best
algorithms over humans, in light of the absolute performance levels of the


Source: Abdi, Hervé - School of Behavioral and Brain Sciences, University of Texas at Dallas


Collections: Biology and Medicine; Computer Technologies and Information Sciences