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Cited by 472

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The Glasgow Face Matching Test

Burton, A. Mike, White, David, McNeill, Allan·2010·Behavior Research Methods
DOI 10.3758/brm.42.1.286
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Crossref · 10.3758/brm.42.1.286

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1 of 1 references verified0 citation errors · 0 not checkable

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  • Facial comparison accuracy and data quality are directly correlated.

    “Facial comparison accuracy and data quality are, thus, directly correlated [95,96], especially in terms of individual accuracy variation across multiple analysts [97] and individual analyst ability overestimation [98].”

    From Forensic Facial Comparison: Current Status, Limitations, and Future Directions (2021) · cites this paper as [97]

    The General Discussion (page unavailable) says the test uses high-quality, well-lit images to avoid making matching artificially difficult and to optimize accuracy. It does not compare levels of data quality or establish a direct correlation between quality and facial-comparison accuracy. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

  • 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 [97]

    The introductory discussion reports that unfamiliar face matching is surprisingly difficult, with 10%–25% errors in studies using pairs of images. The General Discussion also reports substantial variation between individuals, even under favorable conditions. These passages support the general point, but not the unqualified assertion that matching is unreliable “on all accounts.” (LLM, conf=0.82)

    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 [6]

    The opening discussion reports 20–30% errors in some unfamiliar-face array tests, but gives a broader range of 10–25% for paired-face tests. The GFMT results report about 10% mean errors on the full test and about 19% on the short test. No passage establishes a typical 20–30% error rate for trained practitioners. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Studies reported here and in previous work show large and stable individual differences in face matching accuracy that are unrelated to length of professional experience.

    “Studies reported here and in previous work show large and stable individual differences in face matching accuracy that are unrelated to length professional experience [15, 17, 32].”

    From Error Rates in Users of Automatic Face Recognition Software (2015) · cites this paper as [15]

    The General Discussion (page unavailable) reports large interindividual variation in face-matching performance, and A TEST FOR FACE MATCHING (page unavailable) reports high split-half reliability (r = .81). The paper does not establish stability over time or test whether accuracy is unrelated to length of professional experience; its finding of no correlation with age does not address experience. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • The matching of facial identity across two simultaneously presented images is a notoriously difficult task, even under the simplest of circumstances.

    “The matching of facial identity across two simultaneously presented images is a notoriously difficult task, even under the simplest of circumstances (Burton et al., 2010; Megreya & Burton, 2006).”

    From Enhanced Matching of Children’s Faces in “Super-Recognisers” But Not High-Contact Controls (2020) · cites this paper as Burton et al., 2010

    The General Discussion says matching two face images is not trivially easy even under apparently optimal conditions. The introductory discussion reports 10%–25% error rates for pairs of unfamiliar faces, but says performance on familiar faces reaches ceiling levels. The claim omits that familiarity qualification. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 22

  1. Benton, A. L., Hamsher, K. S., Varney, N. R., & Spreen, O. (1983). Contributions to neuropsychological assessment. New York: Oxford University Press.
  2. Bruce, V., Henderson, Z., Greenwood, K., Hancock, P., Burton, A. M., & Miller, P. (1999). Verification of face identities from images captured on video. Journal of Experimental Psychology: Applied, 5, 339–360. · DOI · Paper page
  3. Bruce, V., Henderson, Z., Newman, C., & Burton, A. M. (2001). Matching identities of familiar and unfamiliar faces caught on CCTV images. Journal of Experimental Psychology: Applied, 7, 207–218. · DOI · Paper page
  4. Bruce, V., & Young, A. W. (1986). Understanding face recognition. British Journal of Psychology, 77, 305–327. · DOI
  5. Burton, A. M., Jenkins, R., Hancock, P. J. B., & White, D. (2005). Robust representations for face recognition: The power of averages. Cognitive Psychology, 51, 256–284. · DOI
  6. Clutterbuck, R., & Johnston, R. A. (2002). Exploring levels of face familiarity by using an indirect face-matching measure. Perception, 31, 985–994. · DOI
  7. Clutterbuck, R., & Johnston, R. A. (2004). Matching as an index of face familiarity. Visual Cognition, 11, 857–869. · DOI
  8. Clutterbuck, R., & Johnston, R. A. (2005). Demonstrating how unfamiliar faces become familiar using a face matching task. European Journal of Cognitive Psychology, 17, 97–116. · DOI
  9. Davis, J., & Valentine, T. (2009). CCTV on trial: Matching video images with the defendant in the dock. Applied Cognitive Psychology, 23, 482–505. · DOI · Paper page
  10. Duchaine, B., & Nakayama, K. (2006). The Cambridge Face Memory Test: Results for neurologically intact individuals and an investigation of its validity using inverted face stimuli and prosopagnosic participants. Neuropsychologia, 44, 576–585. · DOI
  11. Hancock, P. J. B., Bruce, V., & Burton, A. M. (2000). Recognition of unfamiliar faces. Trends in Cognitive Sciences, 4, 330–337. · DOI · Paper page
  12. Jenkins, R., & Burton, A. M. (2008). 100% accuracy in automatic face recognition. Science, 319, 435. · DOI
  13. Kagan, J. (1965). Reflection-impulsivity and reading ability in primary grade children. Child Development, 36, 609–628. · DOI
  14. Lane, S. M., & Meissner, C. A. (2008). A “middle road” approach to bridging the basic-applied divide in eyewitness identification research. Applied Cognitive Psychology, 22, 779–787. · DOI
  15. Malpass, R. S., & Devine, P. G. (1981). Eyewitness identification: Lineup instructions and the absence of the offender. Journal of Applied Psychology, 66, 482–489. · DOI
  16. Megreya, A. M., & Burton, A. M. (2006). Unfamiliar faces are not faces: Evidence from a matching task. Memory & Cognition, 34, 865–876. · DOI · Paper page
  17. Megreya, A. M., & Burton, A. M. (2007). Hits and false positives in face matching: A familiarity-based dissociation. Perception & Psychophysics, 69, 1175–1184. · DOI · Paper page
  18. Megreya, A. M., & Burton, A. M. (2008). Matching faces to photographs: Poor performance in eyewitness memory (without the memory). Journal of Experimental Psychology: Applied, 14, 364–372. · DOI
  19. Rossion, B., & Pourtois, G. (2004). Revisiting Snodgrass and Vanderwart’s object set: The role of surface detail in basic-level object recognition. Perception, 33, 217–236. · DOI
  20. Searcy, J. H., Bartlett, J. C., & Memon, A. (1999). Age differences in accuracy and choosing in eyewitness identification and face recognition. Memory & Cognition, 27, 538–552. · DOI
  21. Warrington, E. K. (1984). Recognition Memory Test. Windsor, U.K.: NFER-Nelson.
  22. Wells, G. L., & Olson, E. (2003). Eyewitness identification. Annual Review of Psychology, 54, 277–295.bet 10 · DOI

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Metadata

Authors
Burton, A. M., White, D., & McNeill, A.
Venue
Behavior Research Methods
Publisher
Springer Science and Business Media LLC
Published
2010-02
Volume
42
Issue
1
Pages
286-291
ISSN
  • 1554-351X
  • 1554-3528
DOI
10.3758/brm.42.1.286
Cited by
472
References
1
Language
en
Licence
www.springer.com/tdm (tdm)

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