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Passport Officers’ Errors in Face Matching

White, David, Kemp, Richard I., Jenkins, Rob, Matheson, Michael, Burton, A. Mike·2014·PLoS ONE

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Crossref · 10.1371/journal.pone.0103510

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  • Face age only affected accuracy in target present trials, both here and in previous work, and so does not account for the equivalent error rates observed in target absent arrays.

    “However, face age only affected accuracy in target present trials, both here and in previous work [17, 23], and so does not account for the equivalent error rates we observed in target absent arrays.”

    From Error Rates in Users of Automatic Face Recognition Software (2015) · cites this paper as [17]

    The Photo-to-Photo Test describes older photos and official ID photos as its comparison conditions. Its Results report a significant effect of photo type on mismatch trials—the equivalent of target-absent trials—contrary to the claim that the effect was confined to target-present trials. The citing authors’ own observation of equivalent error rates in their arrays is not attributed to this source. (LLM, conf=0.86)

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    Experimental — accuracy not yet measured
  • Error-rates in tests of unfamiliar face identification typically average 20-30% for both novices and trained practitioners.

    “Error-rates in tests typically average 20–30% for both novices and trained practitioners [5–9].”

    From Do professional facial image comparison training courses work? (2019) · cites this paper as [9]

    The Photo-to-Photo Test Results report 70.9% accuracy on match trials (29.1% errors), with similar performance for passport officers and students. The Glasgow Face Matching Test Results also report 79.2% accuracy for officers (20.8% errors), close to the 81.3% population norm. But officers averaged only 10% errors on the Person-to-Photo Test, so this paper does not establish 20–30% as the typical average across tests. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • Participants in these studies were facial reviewers-non-specialist facial image comparison practitioners who perform fast, high-volume face identifications (e.g. at border control).

    “Instead, participants in these studies were facial reviewers–non-specialist facial image comparison practitioners who perform fast, high-volume face identifications (e.g. at border control).”

    From Do professional facial image comparison training courses work? (2019) · cites this paper as [9]

    The Participants section identifies passport officers who routinely compare people and photographs with ID images, supporting the description of practitioners who perform face identifications. But the Introduction describes them as having specialist training and experience, and the study places them at a passport office, not border control. The copy does not establish that their ordinary work involves fast, high-volume identifications; the ten-second limit in the Person-to-Photo Test describes an experimental task. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • Face aging caused poorer performance compared to similar tasks where images were taken on the same day.

    “To account for this, and consistent with recent work [17, 23] we suggest that face aging caused poorer performance compared to similar tasks where images were taken on the same day [12].”

    From Error Rates in Users of Automatic Face Recognition Software (2015) · cites this paper as [17]

    The Photo-to-Photo Test section says age-related changes affect matching accuracy, and its Results report poor performance when matching newer images to older photos. The Glasgow Face Matching Test section describes a same-day-image task, but the paper does not establish that aging caused poorer performance than on that task; the tasks were not directly compared for this effect. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • Previous research has shown that face aging makes unfamiliar face matching more difficult, increasing error by 20% when images are separated by more than a year.

    “Previous research has shown that face aging makes unfamiliar face matching more difficult, increasing error by 20% when images are separated by more than a year [17, 22, 23] and so we expected error rates to be higher than in similar test using images taken on the same day [12].”

    From Error Rates in Users of Automatic Face Recognition Software (2015) · cites this paper as [17]

    The Photo-to-Photo Test introduction (page unavailable) says age-related changes in appearance have a large effect on matching accuracy. Its Results report poorer matching for some older ID photos, but the paper does not report a 20% increase in errors or establish a threshold of more than one year; it tested photos taken two years apart and ID photos of uncertain age. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

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Citations

Cites

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Research works printed but not linked: 17

  1. V Bruce, 1999, Verification of face identities from images captured on video, J Exp Psychol Appl, 5, 339, 10.1037/1076-898X.5.4.339 · DOI · Paper page
  2. AM Megreya, 2006, Unfamiliar faces are not faces: Evidence from a matching task, Mem Cognition, 34, 865, 10.3758/BF03193433 · DOI · Paper page
  3. AM Burton, 2010, The Glasgow Face Matching Test, Behav Res Methods, 42, 286, 10.3758/BRM.42.1.286 · DOI · Paper page
  4. RI Kemp, 1997, When seeing should not be believing: Photographs, credit cards and fraud, Appl Cognitive Psych, 11, 211, 10.1002/(SICI)1099-0720(199706)11:3<211::AID-ACP430>3.0.CO;2-O · DOI
  5. JP Davis, 2009, CCTV on trial: Matching video images with the defendant in the dock, Appl Cognitive Psych, 23, 482, 10.1002/acp.1490 · DOI · Paper page
  6. AM Megreya, 2008, Matching faces to photographs: Poor performance in eyewitness memory (without the memory), J Exp Psychol Appl, 14, 364, 10.1037/a0013464 · DOI
  7. AM Burton, 1999, Face recognition in poor-quality video: Evidence from security surveillance, Psychol Sci, 10, 243, 10.1111/1467-9280.00144 · DOI · Paper page
  8. P Hancock, 2000, Recognition of unfamiliar faces, Trends Cog Sci, 4, 330, 10.1016/S1364-6613(00)01519-9 · DOI · Paper page
  9. R Jenkins, 2011, Stable face representations, Philos T Roy Soc B, 366, 1671, 10.1098/rstb.2010.0379 · DOI
  10. MM Woodhead, 1979, On training people to recognize faces, Ergonomics, 22, 333, 10.1080/00140137908924617 · DOI · Paper page
  11. Towler A, White D, Kemp RI (2014) Evaluating training methods for facial image comparison: The face shape strategy does not work. Perception: 43, 214–218. · DOI · Paper page
  12. D White, 2014, Feedback training for facial image comparison, Psychon B Rev, 21, 100, 10.3758/s13423-013-0475-3 · DOI · Paper page
  13. AM Megreya, 2013, Matching Face Images Taken on the Same Day or Months Apart: the Limitations of Photo ID, Appl Cognitive Psych, 27, 700, 10.1002/acp.2965 · DOI · Paper page
  14. R Russell, 2009, Super-recognizers: People with extraordinary face recognition ability, Psychon B Rev, 16, 252, 10.3758/PBR.16.2.252 · DOI · Paper page
  15. AM Megreya, 2007, Hits and false positives in face matching: A familiarity-based dissociation, Percept Psychophys, 69, 1175, 10.3758/BF03193954 · DOI · Paper page
  16. T Susilo, 2013, Advances in developmental prosopagnosia research, Curr Opin Neurobiol, 23, 423, 10.1016/j.conb.2012.12.011 · DOI
  17. JB Wilmer, 2010, Human face recognition ability is specific and highly heritable, P Natl Acad Sci USA, 107, 5238, 10.1073/pnas.0913053107 · DOI · Paper page

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Metadata

Authors
White, D., Kemp, R. I., Jenkins, R., Matheson, M., & Burton, A. M.
Venue
PLoS ONE
Published
2014-08-18
Volume
9
Issue
8
Pages
e103510
ISSN
1932-6203
Cited by
241
References
0
Language
en

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