Cited by 233

The DOI matches its Crossref record.

Matching identities of familiar and unfamiliar faces caught on CCTV images

Bruce, Vicki, Henderson, Zoë, Newman, Craig, Burton, A. Mike·2001·Journal of Experimental Psychology: Applied

Abstract

People can be inaccurate at matching unfamiliar faces shown in high-quality video images, even when viewpoint and facial expressions are closely matched. However, identification of highly familiar faces appears good, even when video quality is poor. Experiment 1 reported a direct comparison between familiar and unfamiliar faces. Participants who were personally familiar with target items appearing on video were highly accurate at a verification task. Unfamiliar participants doing the same task performed very inaccurately. Familiarity affected discriminability, but not bias. Experiments 2 and 3 showed that brief periods of familiarization have little beneficial effect unless "deep" or "social" processing is encouraged. The results show that video evidence can be used effectively as a probe to identity when the faces shown are highly familiar to observers, but caution should be used where images of unfamiliar people are being compared.

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Crossref · 10.1037/1076-898x.7.3.207

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  • All forms of facial comparison accuracy will suffer when using low-resolution analogue CCTV images, even if image quality is good in other respects.

    “In general, all forms of facial comparison accuracy will suffer when using low-resolution analogue CCTV images, even if image quality is good in other respects [48,81,93,122].”
  • Unfamiliar face matching is considered complex and unreliable on all accounts.

    “The role of expertise is particularly relevant in FFC, since unfamiliar face matching is considered complex and unreliable on all accounts [97,122].”
  • 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].”
  • Humans are notoriously poor at identifying unfamiliar faces.

    “This lack of empirical validation for facial image comparison training courses is particularly concerning because humans are notoriously poor at identifying unfamiliar faces.”
  • Familiar face matching results in rapid and accurate assessments.

    “Research has repeatedly shown that deciding whether two different face photographs are of the same person, or whether a person standing in front of you is the same person depicted in a photograph, results in rapid and accurate assessments for familiar faces (Bruce et al., 2001) and inaccurate assessments for unfamiliar faces (Bruce et al., 1999, 2001; Kemp, Towell & Pike, 1997; Megreya & Burton, 2”

    From Unfamiliar face matching with photographs of infants and children (2018) · cites this paper as Bruce et al., 2001

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No references could be resolved yet.

Research works printed but not linked: 20

  1. 1997, Adobe Photoshop (Version 4.0.1)
  2. 10.1037/h0037190 · DOI
  3. Bruce, 1982, Changing faces: Visual and non-visual coding processes in face recognition., The British Journal of Psychology, 73, 105, 10.1111/j.2044-8295.1982.tb01795.x · DOI
  4. 10.1037/1076-898X.5.4.339 · DOI · Paper page
  5. 10.1111/1467-9280.00144 · DOI · Paper page
  6. Christie, 1998, The role of movement in the recognition of unfamiliar faces., Memory & Cognition, 26, 780, 10.3758/BF03211397 · DOI
  7. 10.1348/000712600161907 · DOI
  8. Harmon, 1973, Masking in visual recognition: Effects of two dimensional filtered noise., Science, 180, 1194, 10.1126/science.180.4091.1194 · DOI
  9. 10.1002/acp.718 · DOI · Paper page
  10. 10.1037/h0029933 · DOI
  11. 10.1002/(SICI)1099-0720(199706)11:3<211::AID-ACP430>3.0.CO;2-O · DOI
  12. Knight, 1997, The role of movement in face recognition., Visual Cognition, 4, 265, 10.1080/713756764 · DOI
  13. 10.1207/S15326969ECO1204_01 · DOI
  14. 10.1002/1099-0720(200101/02)15:1<101::AID-ACP697>3.0.CO;2-7 · DOI
  15. Lander, 1999, The role of movement in the recognition of familiar faces., Memory & Cognition, 27, 974, 10.3758/BF03201228 · DOI
  16. 10.1037/0278-7393.3.4.406 · DOI
  17. Pike, 1997, Recognizing moving faces: The relative contribution of motion and perspective view information., Visual Cognition, 4, 409, 10.1080/713756769 · DOI
  18. Pollack, 1964, A non-parametric analysis of recognition experiments., Psychonomic Science, 1, 125, 10.3758/BF03342823 · DOI
  19. 10.1037/0003-066X.48.5.553 · DOI
  20. 10.1037/0278-7393.7.3.181 · DOI

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Metadata

Authors
Bruce, V., Henderson, Z., Newman, C., & Burton, A. M.
Venue
Journal of Experimental Psychology: Applied
Published
2001
Volume
7
Issue
3
Pages
207-218
ISSN
  • 1939-2192
  • 1076-898X
Cited by
233
References
0
Language
en

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