Skip to main content
U.S. flag

An official website of the United States government

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.

The Good, the Bad, and the Ugly Face 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. The base veri cation rate (VR) is 0.98 at a false accept rate (FAR) of 0.001. The Bad partition contains pairs of images of average diculty 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 diffcult 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 a result of how a face is presented in each image.
Citation
Image and Vision Computing

Keywords

face recognition, challenge problem

Citation

Phillips, P. , Beveridge, J. , Draper, B. , Givens, G. , O'Toole, A. , Bolme, D. , Dunlop, J. , Lui, Y. , Sahibzada, H. and Weimer, S. (2012), The Good, the Bad, and the Ugly Face Challenge Problem, Image and Vision Computing, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=910476 (Accessed February 20, 2024)
Created November 20, 2012, Updated February 19, 2017