The FERET evaluation methodology for face-recognition algorithms
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...
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| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence 2000-10, Vol.22 (10), p.1090-1104 |
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| container_title | IEEE transactions on pattern analysis and machine intelligence |
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| creator | Phillips, P.J. Hyeonjoon Moon Rizvi, S.A. Rauss, P.J. |
| description | 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. |
| doi_str_mv | 10.1109/34.879790 |
| format | Article |
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| ispartof | IEEE transactions on pattern analysis and machine intelligence, 2000-10, Vol.22 (10), p.1090-1104 |
| issn | 0162-8828 1939-3539 |
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| source | IEEE Explore |
| subjects | Algorithms Area measurement Face recognition Facial Image databases Intelligence Pattern analysis State of the art System testing |
| title | The FERET evaluation methodology for face-recognition algorithms |
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