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Preliminary Studies on the Good, the Bad, and the Ugly Face Recognition Challenge Problem

Published

Author(s)

P J. Phillips, J. R. Beveridge, David Bolme, Bruce A. Draper, Yui M. Lui

Abstract

Face recognition has made significant advances over the last twenty years. State-of-the-art algorithms push the performanceenvelope to near perfect recognition rates on many face databases. Recently, the Good, the Bad, and the Ugly (GBU) face challenge problem has been introduced to focus on hard aspects of face recognition from still frontal images. In this paper, we introduce the CohortLDA base- line algorithm, which is an Linear Discriminant Analysis (LDA) algorithm with color spaces and cohort normalization. CohortLDA greatly outperforms some well known face recognition algorithms on the GBU challenge problem. The GBU protocol includes rules for creating training sets. We investigate the effect on performance of violating the rules for creating training sets. This analysis shows that violating the GBU protocol can substantially over estimate performance on the GBU challenge problem.
Conference Dates
June 18, 2012
Conference Location
Providence, RI
Conference Title
IEEE Computer Society Workshop on Biometrics

Keywords

face recognition, biometrics, algorithms

Citation

Phillips, P. , Beveridge, J. , Bolme, D. , Draper, B. and Lui, Y. (2012), Preliminary Studies on the Good, the Bad, and the Ugly Face Recognition Challenge Problem, IEEE Computer Society Workshop on Biometrics, Providence, RI, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=911435 (Accessed April 12, 2024)
Created November 26, 2012, Updated February 19, 2017