CoChat
Sign Up
Cited by 3,692

The DOI matches its Crossref record.

The FERET evaluation methodology for face-recognition algorithms

Phillips, P.J., Hyeonjoon Moon, Rizvi, S.A., Rauss, P.J.·2000·IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI 10.1109/34.879790
Open this paper in CoChat — free account

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.

Overview

Integrity signals

Registry

Crossref · 10.1109/34.879790

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The FISWG feature list includes 18 facial components, each with associated descriptors, as well as a nineteenth descriptive component for use with uncategorized features.

    “This list includes 18 facial components, each with associated descriptors, as well as a nineteenth descriptive component for use with uncategorized features [51,54].”

    From Forensic Facial Comparison: Current Status, Limitations, and Future Directions (2021) · cites this paper as [51]

  • The FISWG feature list is the most exhaustive list available, including over 130 facial component characteristics and over 290 characteristic descriptors.

    “The FISWG feature list is also the most exhaustive list available, including over 130 facial component characteristics and over 290 characteristic descriptors [51].”

    From Forensic Facial Comparison: Current Status, Limitations, and Future Directions (2021) · cites this paper as [51]

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 15

  1. 10.1109/CVPR.1996.517140 · DOI
  2. 10.1364/JOSAA.14.001724 · DOI
  3. 10.1007/978-3-642-72201-1_4 · DOI
  4. 10.1109/AFGR.1998.670971 · DOI
  5. phillips, 1997, the face recognition technology (feret) program, Proc Office of Nat l Drug Control Policy CTAC Int l Technology Symp, 8
  6. 10.1162/jocn.1991.3.1.71 · DOI · Paper page
  7. 10.1016/S0262-8856(97)00070-X · DOI
  8. 10.1109/34.531802 · DOI
  9. 10.1109/34.598235 · DOI
  10. 10.1109/34.598227 · DOI
  11. moon, 1998, analysis of pca-based face recognition algorithms, Empirical Evaluation Techniques in Computer Vision, 57
  12. wilder, 1994, face recognition using transform coding of grayscale projection projections and the neural tree network, Artifical Neural Networks with Applications in Speech and Vision, 520
  13. rauss, 1996, the feret (face recognition technology) program, Surveillance and Assessment Technology for Law Enforcement SPIE, 2, 2
  14. rizvi, 0, the feret verification testing protocol for face recognition algorithms, Image Vision Computing
  15. rizvi, 1998, the feret verification testing protocol for face recognition algorithms, 10.6028/NIST.IR.6281 · DOI

Cited by

Sorted by citations

Metadata

Authors
Phillips, P. J., Moon, H., Rizvi, S. A., & Rauss, P. J.
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2000
Volume
22
Issue
10
Pages
1090-1104
ISSN
0162-8828
DOI
10.1109/34.879790
Cited by
3,692
References
0
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review