Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems. The Face Recognition Technology (FERET) program has addressed both issues through the FERET database of facial images and the establishment of the FERET tests. To date, 14,126 images from 1,199 individuals are included in the FERET database, which is divided into development and sequestered portions of the database. In September 1996, the FERET program administered the third in a series of FERET face-recognition tests. The primary objectives of the third test were to 1) assess the state of the art, 2) identify future areas of research, and 3) measure algorithm performance.
Description
IEEE Xplore Abstract - The FERET evaluation methodology for face-recognition algorithms
%0 Journal Article
%1 879790
%A Phillips, P. J.
%A Moon, Hyeonjoon
%A Rizvi, S. A.
%A Rauss, P. J.
%D 2000
%J IEEE Transactions on Pattern Analysis and Machine Intelligence
%K benchmark database face_recognition
%N 10
%P 1090-1104
%R 10.1109/34.879790
%T The FERET evaluation methodology for face-recognition algorithms
%U http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=879790
%V 22
%X Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems. The Face Recognition Technology (FERET) program has addressed both issues through the FERET database of facial images and the establishment of the FERET tests. To date, 14,126 images from 1,199 individuals are included in the FERET database, which is divided into development and sequestered portions of the database. In September 1996, the FERET program administered the third in a series of FERET face-recognition tests. The primary objectives of the third test were to 1) assess the state of the art, 2) identify future areas of research, and 3) measure algorithm performance.
@article{879790,
abstract = {Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems. The Face Recognition Technology (FERET) program has addressed both issues through the FERET database of facial images and the establishment of the FERET tests. To date, 14,126 images from 1,199 individuals are included in the FERET database, which is divided into development and sequestered portions of the database. In September 1996, the FERET program administered the third in a series of FERET face-recognition tests. The primary objectives of the third test were to 1) assess the state of the art, 2) identify future areas of research, and 3) measure algorithm performance.},
added-at = {2016-07-29T18:18:28.000+0200},
author = {Phillips, P. J. and Moon, Hyeonjoon and Rizvi, S. A. and Rauss, P. J.},
biburl = {https://www.bibsonomy.org/bibtex/22c05516713a39754979de143fb97ab2b/alex_ruff},
description = {IEEE Xplore Abstract - The FERET evaluation methodology for face-recognition algorithms},
doi = {10.1109/34.879790},
interhash = {2f1c64e5f105312c524cf744452d77fa},
intrahash = {2c05516713a39754979de143fb97ab2b},
issn = {0162-8828},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
keywords = {benchmark database face_recognition},
month = oct,
number = 10,
pages = {1090-1104},
timestamp = {2016-07-29T18:18:28.000+0200},
title = {The FERET evaluation methodology for face-recognition algorithms},
url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=879790},
volume = 22,
year = 2000
}