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Research Article

Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms

View ORCID ProfileP. Jonathon Phillips, Amy N. Yates, Ying Hu, Carina A. Hahn, Eilidh Noyes, Kelsey Jackson, Jacqueline G. Cavazos, Géraldine Jeckeln, Rajeev Ranjan, Swami Sankaranarayanan, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa, David White, and Alice J. O’Toole
  1. aInformation Access Division, National Institute of Standards and Technology, Gaithersburg, MD 20899;
  2. bSchool of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX 75080;
  3. cDepartment of Electrical and Computer Engineering, University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20854;
  4. dUniversity of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20854;
  5. eSchool of Psychology, The University of New South Wales, Sydney, NSW 2052, Australia

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PNAS June 12, 2018 115 (24) 6171-6176; first published May 29, 2018; https://doi.org/10.1073/pnas.1721355115
P. Jonathon Phillips
aInformation Access Division, National Institute of Standards and Technology, Gaithersburg, MD 20899;
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  • ORCID record for P. Jonathon Phillips
  • For correspondence: jonathon@nist.gov
Amy N. Yates
aInformation Access Division, National Institute of Standards and Technology, Gaithersburg, MD 20899;
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Ying Hu
bSchool of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX 75080;
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Carina A. Hahn
bSchool of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX 75080;
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Eilidh Noyes
bSchool of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX 75080;
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Kelsey Jackson
bSchool of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX 75080;
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Jacqueline G. Cavazos
bSchool of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX 75080;
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Géraldine Jeckeln
bSchool of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX 75080;
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Rajeev Ranjan
cDepartment of Electrical and Computer Engineering, University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20854;
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Swami Sankaranarayanan
cDepartment of Electrical and Computer Engineering, University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20854;
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Jun-Cheng Chen
dUniversity of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20854;
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Carlos D. Castillo
dUniversity of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20854;
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Rama Chellappa
cDepartment of Electrical and Computer Engineering, University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20854;
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David White
eSchool of Psychology, The University of New South Wales, Sydney, NSW 2052, Australia
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Alice J. O’Toole
bSchool of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX 75080;
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  1. Edited by Thomas D. Albright, The Salk Institute for Biological Studies, La Jolla, CA, and approved April 30, 2018 (received for review December 13, 2017)

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Article Information

vol. 115 no. 24 6171-6176
DOI: 
https://doi.org/10.1073/pnas.1721355115
PubMed: 
29844174

Published By: 
National Academy of Sciences
Print ISSN: 
0027-8424
Online ISSN: 
1091-6490
History: 
  • Published in issue June 12, 2018.
  • Published first May 29, 2018.

Article Versions

  • Previous version (May 29, 2018 - 08:11).
  • You are viewing the most recent version of this article.
Copyright & Usage: 
Copyright © 2018 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

Author Information

  1. P. Jonathon Phillipsa,1,
  2. Amy N. Yatesa,
  3. Ying Hub,
  4. Carina A. Hahnb,
  5. Eilidh Noyesb,
  6. Kelsey Jacksonb,
  7. Jacqueline G. Cavazosb,
  8. Géraldine Jeckelnb,
  9. Rajeev Ranjanc,
  10. Swami Sankaranarayananc,
  11. Jun-Cheng Chend,
  12. Carlos D. Castillod,
  13. Rama Chellappac,
  14. David Whitee, and
  15. Alice J. O’Tooleb
  1. aInformation Access Division, National Institute of Standards and Technology, Gaithersburg, MD 20899;
  2. bSchool of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX 75080;
  3. cDepartment of Electrical and Computer Engineering, University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20854;
  4. dUniversity of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20854;
  5. eSchool of Psychology, The University of New South Wales, Sydney, NSW 2052, Australia
  1. Edited by Thomas D. Albright, The Salk Institute for Biological Studies, La Jolla, CA, and approved April 30, 2018 (received for review December 13, 2017)

Footnotes

  • ↵1To whom correspondence should be addressed. Email: jonathon{at}nist.gov.
  • Author contributions: P.J.P., A.N.Y., D.W., and A.J.O. designed research; R.R., S.S., J.-C.C., C.D.C., and R.C. contributed new reagents/analytic tools; P.J.P., A.N.Y., Y.H., C.A.H., E.N., K.J., J.G.C., G.J., and A.J.O. analyzed data; R.R., S.S., J.-C.C., C.D.C., and R.C. implemented and ran the face recognition algorithms; and P.J.P. and A.J.O. wrote the paper.

  • Conflict of interest statement: The University of Maryland is filing a US patent application that will cover portions of algorithms A2017a and A2017b. R.R., C.D.C., and R.C. are coinventors on this patent.

  • This article is a PNAS Direct Submission.

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1721355115/-/DCSupplemental.

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Article usage

Article usage: May 2018 to April 2021

AbstractFullPdf
May 201819751703376
Jun 201853263654988
Jul 201823201435310
Aug 20181209888271
Sep 2018997930229
Oct 2018148870234
Nov 2018491050233
Dec 201859802282
Total 201812083113322923
Jan 201949572199
Feb 2019851741270
Mar 20191171029225
Apr 2019129712264
May 2019119720257
Jun 201990528155
Jul 201983526155
Aug 201967620174
Sep 2019102567247
Oct 2019125747230
Nov 201992738199
Dec 201989669190
Total 2019114791692565
Jan 2020248844223
Feb 2020117872203
Mar 202076827215
Apr 20201811020361
May 202090737168
Jun 202096659164
Jul 202053586157
Aug 202069499141
Sep 202096655179
Oct 2020149843231
Nov 2020143808278
Dec 2020119583219
Total 2020143789332539
Jan 2021178794235
Feb 2021100641197
Mar 2021169759269
Apr 20215627988
Total 20215032473789
Total15170319078816
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Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms
P. Jonathon Phillips, Amy N. Yates, Ying Hu, Carina A. Hahn, Eilidh Noyes, Kelsey Jackson, Jacqueline G. Cavazos, Géraldine Jeckeln, Rajeev Ranjan, Swami Sankaranarayanan, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa, David White, Alice J. O’Toole
Proceedings of the National Academy of Sciences Jun 2018, 115 (24) 6171-6176; DOI: 10.1073/pnas.1721355115

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Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms
P. Jonathon Phillips, Amy N. Yates, Ying Hu, Carina A. Hahn, Eilidh Noyes, Kelsey Jackson, Jacqueline G. Cavazos, Géraldine Jeckeln, Rajeev Ranjan, Swami Sankaranarayanan, Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa, David White, Alice J. O’Toole
Proceedings of the National Academy of Sciences Jun 2018, 115 (24) 6171-6176; DOI: 10.1073/pnas.1721355115
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