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.

PUBLICATIONS

Transformation, Ranking, and Clustering for Face Recognition Algorithm Performance

Published

Author(s)

Stefan D. Leigh, Nathanael A. Heckert, Andrew L. Rukhin, P J. Phillips, Patrick J. Grother, E M. Newton, M Moody, K Kniskern, S Heath

Abstract

The performance of face recognition algorithms is recently of increased interest, although to date empirical analyses of algorithms have been limited to rank-based scores such a cumulative match score and receiver operating characteristic. This paper demonstrates that algorithms that report ratio scale similarities between unknown and gallery images can be enormalized so that a large body of classical statistical methods can be applied to measure recognition performance.
Citation
Automatic Identification Advanced Technologies Workshop
Pub Type
Journals

Keywords

ANOVA, biometric evaluation, face recognition

Citation

Leigh, S. , Heckert, N. , Rukhin, A. , Phillips, P. , Grother, P. , Newton, E. , Moody, M. , Kniskern, K. and Heath, S. (2002), Transformation, Ranking, and Clustering for Face Recognition Algorithm Performance, Automatic Identification Advanced Technologies Workshop (Accessed October 10, 2024)

Issues

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

Created January 1, 2002, Updated February 17, 2017