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An Introduction to the Good, the Bad, & the Ugly Face Recognition Challenge Problem

Published

Author(s)

P J. Phillips, J. R. Beveridge, Bruce A. Draper, Geof H. Givens, Alice J. O'Toole, David Bolme, Joseph Dunlop, Yui M. Lui, Hassan A. Sahibzada, Samuel Weimer

Abstract

The Good, the Bad, & the Ugly Face Challenge Problem was created to encourage the development of algorithms that are robust to recognition across changes that occur in still frontal faces. The Good, the Bad, & the Ugly consists of three partitions. The Good partition contains pairs of images that are considered easy to recognize. On the Good partition, the base verification rate (VR) is 0.98 at a false accept rate (FAR) of 0.001. The Bad partition contains pairs of images of average difficulty to recognize. For the Bad partition, the VR is 0.80 at a FAR of 0.001. The Ugly partition contains pairs of images considered difficult to recognize, with a VR of 0.15 at a FAR of 0.001. The base performance is from fusing the output of three of the top performers in the FRVT 2006. The design of the Good, the Bad, & the Ugly controls for pose variation, subject aging, and subject recognizability. Subject recognizability is controlled by having the same number of images of each subject in every partition. This implies that the differences in performance among the partitions are result of how a face is presented in each image.
Proceedings Title
The Ninth IEEE International Conference on Automatic Face and Gesture Recognition (FG 2011)
Conference Dates
March 21-25, 2011
Conference Location
Santa Barbara, CA

Citation

Phillips, P. , Beveridge, J. , Draper, B. , Givens, G. , O'Toole, A. , Bolme, D. , Dunlop, J. , Lui, Y. , Sahibzada, H. and Weimer, S. (2011), An Introduction to the Good, the Bad, & the Ugly Face Recognition Challenge Problem, The Ninth IEEE International Conference on Automatic Face and Gesture Recognition (FG 2011), Santa Barbara, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=907861 (Accessed July 16, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created March 16, 2011, Updated February 19, 2017