The DOI matches its Crossref record.
Matching identities of familiar and unfamiliar faces caught on CCTV images
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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
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].”
From Forensic Facial Comparison: Current Status, Limitations, and Future Directions (2021) · cites this paper as [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].”
From Forensic Facial Comparison: Current Status, Limitations, and Future Directions (2021) · cites this paper as [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].”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [8]
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.”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [8]
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
Face matching performance declines for unfamiliar compared with familiar face pairs.
“The performance declines for unfamiliar compared with familiar face pairs (Bruce et al., 2001)”
From Enhanced Matching of Children’s Faces in “Super-Recognisers” But Not High-Contact Controls (2020) · cites this paper as Bruce et al., 2001
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 20
- 1997, Adobe Photoshop (Version 4.0.1)
- 10.1037/h0037190 · DOI
- 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
- 10.1037/1076-898X.5.4.339 · DOI · Paper page
- 10.1111/1467-9280.00144 · DOI · Paper page
- Christie, 1998, The role of movement in the recognition of unfamiliar faces., Memory & Cognition, 26, 780, 10.3758/BF03211397 · DOI
- 10.1348/000712600161907 · DOI
- Harmon, 1973, Masking in visual recognition: Effects of two dimensional filtered noise., Science, 180, 1194, 10.1126/science.180.4091.1194 · DOI
- 10.1002/acp.718 · DOI · Paper page
- 10.1037/h0029933 · DOI
- 10.1002/(SICI)1099-0720(199706)11:3<211::AID-ACP430>3.0.CO;2-O · DOI
- Knight, 1997, The role of movement in face recognition., Visual Cognition, 4, 265, 10.1080/713756764 · DOI
- 10.1207/S15326969ECO1204_01 · DOI
- 10.1002/1099-0720(200101/02)15:1<101::AID-ACP697>3.0.CO;2-7 · DOI
- Lander, 1999, The role of movement in the recognition of familiar faces., Memory & Cognition, 27, 974, 10.3758/BF03201228 · DOI
- 10.1037/0278-7393.3.4.406 · DOI
- Pike, 1997, Recognizing moving faces: The relative contribution of motion and perspective view information., Visual Cognition, 4, 409, 10.1080/713756769 · DOI
- Pollack, 1964, A non-parametric analysis of recognition experiments., Psychonomic Science, 1, 125, 10.3758/BF03342823 · DOI
- 10.1037/0003-066X.48.5.553 · DOI
- 10.1037/0278-7393.7.3.181 · DOI
Cited by
Sorted by citations
(2016) · doi:10.3389/fpsyg · Cited by 801
Do professional facial image comparison training courses work?
Towler, A., Kemp, R. I., Burton, A. M., Dunn, J. D., Wayne, T., Moreton, R., & White, D. (2019) · PLOS ONE · doi:10.1371/journal.pone.0211037 · Cited by 111
Self-citationThe cognitive and neural development of face recognition in humans
McKone, E., Crookes, K., & Kanwisher, N. (2009) · The Cognitive Neurosciences · doi:10.7551/mitpress/8029.003.0042 · Cited by 77
Face morphing attacks: Investigating detection with humans and computers
Kramer, R. S. S., Mireku, M. O., Flack, T. R., & Ritchie, K. L. (2019) · Cognitive Research: Principles and Implications · doi:10.1186/s41235-019-0181-4 · Cited by 48
Forensic Facial Comparison: Current Status, Limitations, and Future Directions
Bacci, N., Davimes, J. G., Steyn, M., & Briers, N. (2021) · Biology · doi:10.3390/biology10121269 · Cited by 26
Validation of forensic facial comparison by morphological analysis in photographic and CCTV samples
Bacci, N., Houlton, T. M. R., Briers, N., & Steyn, M. (2021) · International Journal of Legal Medicine · doi:10.1007/s00414-021-02512-3 · Cited by 23
Unfamiliar face matching with photographs of infants and children
Kramer, R. S. S., Mulgrew, J., & Reynolds, M. G. (2018) · PeerJ · doi:10.7717/peerj.5010 · Cited by 15
Finding Makhubu: A morphological forensic facial comparison
Houlton, T. M. R., & Steyn, M. (2018) · Forensic Science International · doi:10.1016/j.forsciint.2018.01.022 · Cited by 13
Enhanced Matching of Children’s Faces in “Super-Recognisers” But Not High-Contact Controls
Bate, S., Bennetts, R., Murray, E., & Portch, E. (2020) · i-Perception · doi:10.1177/2041669520944420 · Cited by 12
A criterion-placement theory of face matching
Baker, K. A., Mondloch, C. J., Hancock, P. J. B., & Bindemann, M. (2026) · Cognition · doi:10.1016/j.cognition.2025.106319 · Cited by 5
Metadata
- Authors
- Bruce, V., Henderson, Z., Newman, C., & Burton, A. M.
- ORCID
- Burton, A. Mike
- 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
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