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School of Behavioral and Brain Sciences - The University of Texas at Dallas

School of Behavioral and Brain Sciences

Research Projects

Face Recognition Comparisons Between Humans and Machines

 

The performance of state-of-the-art computer-based face recognition systems is tested periodically by researchers at the National Institute of Standards and Technology (NIST). In these tests, competing algorithms from commercial and academic researchers are evaluated and compared on a variety of performance criteria. Remarkably little is know about how the performance of these algorithms compares to human performance. Humans are considered by many to be experts at the task of face recognition. In our work, we have undertaken a number of human-machine comparisons, using algorithms from the NIST competitions as source data. Our work has been carried out in collaboration with researchers at NIST and has produced data that are useful for benchmarking the performance state of the art machine-based face recognition systems against humans.   This work has been funded continuously since 2003 by TSWG/DOD and has been reported in the following recent peer-reviewed papers.

 

O’Toole, A. J. & Natu, V. (2013, accepted). Computational perspectives on the other race effect. Visual Cognition.

 

Rice, A., Phillips, P. J., Natu, V., An, X., & O’Toole, A. J. (in press). Unaware person recognition from the body when face identification fails. Psychological Science.

 

Phillips, P. J., Beveridge, J. R., Draper, B. A., Givens, G., O’Toole, A. J., Bolme, D., Dunlop, J., Lui, Y. M., Sahizada, H. & Wiemer, S. (2012). An Introduction to the Good, Bad, & Ugly Challenge Problem. Image & Vision Computing, 30(3), 177-185.

 

O’Toole, A.J., An, X., Dunlop, J.P., Natu, V. & Phillips, P.J. (2012). Comparing face recognition algorithms to humans on challenging tasks. ACM Transactions on Applied Perception. 9(4), Article 16.

 

O’Toole, A. J., Phillips, P.J., An, X. & Dunlop, J. (2012). Demographic effects on estimates of automatic face recognition. Image & Vision Computing 30(3),169-176.

 

O’Toole, A. J.  (2011). A comparative examination of face recognition by humans and machines. In (Eds. S. Li & A. Jain). Handbook of Face Recognition (2nd Edition). Springer-Verlag, London Ltd., UK.

 

Phillips, P.J., Beveridge, J. R., Draper, B. A., Givens, G., O’Toole, A. J., Bolme, D. Dunlop, J. Lui, Y. M. Sahizada, H. & Wiemer, S. (2011). An Introduction to the Good, Bad, & Ugly Challenge Problem. Proceedings of the 9th IEEE International Conference on Automatic Face and Gesture Recognition.

 

Phillips, P.J., Narvekar, A., Jiang, F. & O’Toole, A. J. (2010). An other-race effect for face recognition algorithms. ACM Transactions on Applied Perception, 8(2), ART 14.


Phillips, P.J., Scruggs, W. T., O’Toole, A. J., Flynn, P. J., Bowyer, K. W., Schott, C. L., Sharpe, M. (2010). Face Recognition Vendor Test 2006 and Iris Challenge Evaluation 2006 large-scale experimental results. IEEE: Transactions on Pattern Analysis and Machine Intelligence, 32(5), 831-846.


Phillips, P.J., Flynn, P. J., Beveridge, R., Scruggs, W. T., O’Toole, A. J., Bolme, D., Bowyer, K. W., Givens, G. H., Lui, Y.M., Sahibzada, H. Scallan, J. Weimer, S. (2009). Overview of the Multiple Biometrics Grand Challenge. Proceedings of the 3rd International Conference on Biometrics, 2009.


O’Toole, A. J., Phillips, P.J., Narvekar, A. (2008). Humans versus algorithms: Comparisons from the Face Recognition Vendor Test 2006. Proceedings of the 8th IEEE International Conference on Automatic Face and Gesture Recognition.


O’Toole, A. J., Phillips, P. J., Jiang, F., Ayyad, J., Pénard, N., & Abdi, H. (2007). Face recognition algorithms surpass humans matching faces across changes in illumination. IEEE: Transactions on Pattern Analysis and Machine Intelligence, 29(9),1642-1646.


O’Toole, A.J., Abdi, H., Jiang, F. & Phillips, P.J. (2007). Fusing face recognition algorithms and humans. IEEE: Transactions on Systems, Man & Cybernetics, 37(5), 1149-1155.


O’Toole, A. J., Harms, J., Snow, S. L., Hurst, D. R., Pappas, M. R. & Abdi, H. (2005). A video database of moving faces and people. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(5), 812-816.

 

 

 

More Research Projects

 

Functional Neuroimaging of High Level Visual Processing of Human FacesFunctional Neuroimaging of High Level Visual Processing of Human Faces

 

Perception and Memory for Human FacesPerception and Memory for Human Faces

 

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