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Cited by 9

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Face identification in the laboratory and in virtual worlds

Bindemann, Markus, Fysh, Matthew C., Trifonova, Iliyana V., Allen, John, McCall, Cade, Burton, A. Mike·2022·Journal of Applied Research in Memory and Cognition
DOI 10.1016/j.jarmac.2021.07.010
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Crossref · 10.1016/j.jarmac.2021.07.010

Cites

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  • Criterion is influenced by the applied context in which face matching is studied.

    “as well as the applied context in which face matching is studied (e.g., Bindemann et al., 2022;Feng & Burton, 2019, 2021;McCaffery & Burton, 2016;Tummon et al., 2019)”

    From A criterion-placement theory of face matching (2026) · cites this paper as Bindemann et al., 2022

  • Criterion shifts in face matching have been observed under a range of conditions, including airport context, costs/payoffs/unequal base rates, and superficial image differences.

    “Criterion shifts have been observed under a range of conditions, for example, when face matching is performed in an airport context (Bindemann et al., 2022), in response to costs, payoffs and unequal base rates (Baker & Bindemann, 2025;Stabile et al., 2024”

    From A criterion-placement theory of face matching (2026) · cites this paper as Bindemann et al., 2022

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Research works printed but not linked: 37

  1. Alenezi, 2013, The effect of feedback on face-matching accuracy, Applied Cognitive Psychology, 27, 735, 10.1002/acp.2968 · DOI · Paper page
  2. Alenezi, 2015, Face matching in a long task: Enforced rest and desk-switching cannot maintain identification accuracy, PeerJ, 3, 1
  3. Anwyl-Irvine, 2020, Gorilla in our midst: An online behavioral experiment builder, Behavior Research Methods, 52, 388, 10.3758/s13428-019-01237-x · DOI
  4. Bailenson, J., Beall, A., & Blascovich, J. (2003). Using virtual heads for person identification: An empirical study comparing photographs to photogrammetrically-generated models. Journal of Forensic Identification, 53(6), 722–728.
  5. Bailenson, 2008, The effects of witness viewpoint distance, angle, and choice on eyewitness accuracy in police lineups conducted in immersive virtual environments, Presence: Teleoperators and Virtual Environments, 17, 242, 10.1162/pres.17.3.242 · DOI
  6. Bate, 2018, Applied screening tests for the detection of superior face recognition, Cognitive Research: Principles and Implications, 3(22), 1
  7. Bindemann, M. (2021). Forensic face matching: Research and practice. Oxford University Press. · DOI
  8. Bindemann, 2016, Matching faces against the clock, i-Perception, 7, 1, 10.1177/2041669516672219 · DOI
  9. Bruce, V., & Young, A. W. (1998). In the eye of the beholder: The science of face perception. Oxford University Press.
  10. Bülthoff, 2019, Face recognition of full-bodied avatars by active observers in a virtual environment, Vision Research, 157, 242, 10.1016/j.visres.2017.12.001 · DOI
  11. Burton, 2010, The Glasgow Face Matching Test, Behavior Research Methods, 42, 286, 10.3758/BRM.42.1.286 · DOI · Paper page
  12. Cole, 2016, Real person interaction in visual attention research, European Psychologist, 21, 141, 10.1027/1016-9040/a000243 · DOI
  13. Feng, 2019, Identity documents bias face matching, Perception, 48, 1163, 10.1177/0301006619877821 · DOI · Paper page
  14. Feng, 2021, Understanding the document bias in face matching, Quarterly Journal of Experimental Psychology, 10.1177/17470218211017902 · DOI
  15. Fysh, 2017, Effects of time pressure and time passage on face matching accuracy, Royal Society Open Science, 4, 1
  16. Fysh, 2018, The Kent Face Matching Test, British Journal of Psychology, 109, 219, 10.1111/bjop.12260 · DOI · Paper page
  17. Fysh, 2020, Differences between and within individuals, and subprocesses of face cognition: Implications for theory, research and personnel selection, Royal Society Open Science, 7, 1
  18. Fysh, 2021, Avatars with faces of real people: A construction method for scientific experiments in virtual reality, Behavior Research Methods, 10.3758/s13428-021-01676-5 · DOI
  19. Hautus, 1995, Corrections for extreme proportions and their biasing effects on estimated values of d′, Behavior Research Methods, Instruments, & Computers, 27, 46, 10.3758/BF03203619 · DOI
  20. Hayward, 2017, Staring reality in the face: A comparison of social attention across laboratory and real-world measures suggests little common ground, Canadian Journal of Experimental Psychology, 71, 212, 10.1037/cep0000117 · DOI
  21. Hole, G. J., & Bourne, V. (2010). Face processing: Psychological, neuropsychological, and applied perspectives. Oxford University Press.
  22. Lander, 2018, Use-inspired basic research on individual differences in face identification: Implications for criminal investigation and security, Cognitive Research: Principles and Implications, 3, 1
  23. McCaffery, 2016, Passport checks: Interactions between matching faces and biographical details, Applied Cognitive Psychology, 30, 925, 10.1002/acp.3281 · DOI · Paper page
  24. McCall, 2009, How, when, and why to use digital experimental virtual environments to study social behavior, Social and Personality Psychology Compass, 3, 744, 10.1111/j.1751-9004.2009.00195.x · DOI
  25. McCall, 2016, Introducing the Wunderkammer as a tool for emotion research: Unconstrained gaze and movement patterns in three emotionally evocative virtual worlds, Computers in Human Behavior, 59, 93, 10.1016/j.chb.2016.01.028 · DOI
  26. Papesh, 2018, The low-prevalence effect in unfamiliar face-matching: The roles of feedback and criterion shifting, Journal of Experimental Psychology: Applied, 24, 416
  27. Peirce, 2007, PsychoPy - Psychophysics software in Python, Journal of Neuroscience Methods, 162, 8, 10.1016/j.jneumeth.2006.11.017 · DOI
  28. Phillips, 2018, Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms, Proceedings of the National Academy of Sciences, 115, 6171, 10.1073/pnas.1721355115 · DOI · Paper page
  29. Ramon, 2021, Super-Recognizers – a novel diagnostic framework, 70 cases, and guidelines for future work, Neuropsychologia, 158, 1
  30. Ramon, 2019, Super-recognizers: From the lab to the world and back again, British Journal of Psychology, 110, 461, 10.1111/bjop.12368 · DOI
  31. Skarratt, 2012, Visual cognition during real social interaction, Frontiers in Human Neuroscience, 6, 1
  32. Stanislaw, 1999, Calculation of signal detection theory measures, Behavior Research Methods, Instruments, & Computers, 31, 137, 10.3758/BF03207704 · DOI · Paper page
  33. Tummon, 2019, Facial identification at a virtual reality airport, i-Perception, 10, 1, 10.1177/2041669519863077 · DOI
  34. Tummon, 2020, Body language influences on facial identification at passport control: An exploration in virtual reality, i-Perception, 11, 1, 10.1177/2041669520958033 · DOI
  35. White, D., Kemp, R. I., Jenkins, R., Matheson, M., & Burton, A. M. (2014). Passport officers’ errors in face matching. PLoS ONE, 9(8), e103510. https://doi.org/10.1371/journal.pone.0103510 · DOI · Paper page
  36. Wilson, C. J., & Soranzo, A. (2015). The use of virtual reality in psychology: A case study in visual perception. Computational and Mathematical Methods in Medicine, 1–7, 151702. https://doi.org/10.1155/2015/151702 · DOI · Paper page
  37. Wirth, 2017, An easy game for frauds? Effects of professional experience and time pressure on passport-matching performance, Journal of Experimental Psychology: Applied, 23, 138

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Metadata

Authors
Bindemann, M., Fysh, M. C., Trifonova, I. V., Allen, J., McCall, C., & Burton, A. M.
ORCID
Venue
Journal of Applied Research in Memory and Cognition
Publisher
American Psychological Association (APA)
Published
2022-03
Volume
11
Issue
1
Pages
120-134
ISSN
  • 2211-369X
  • 2211-3681
DOI
10.1016/j.jarmac.2021.07.010
Cited by
9
References
3
Language
en
Update notices
correction (2022-09-29)
Licence
creativecommons.org/licenses/by/3.0/ (vor)
Funders
Economic and Social Research Council (ES/S010181/1)

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