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Face Recognition by Metropolitan Police Super-Recognisers - PubMed

  • ️Fri Jan 01 2016

Face Recognition by Metropolitan Police Super-Recognisers

David J Robertson et al. PLoS One. 2016.

Abstract

Face recognition is used to prove identity across a wide variety of settings. Despite this, research consistently shows that people are typically rather poor at matching faces to photos. Some professional groups, such as police and passport officers, have been shown to perform just as poorly as the general public on standard tests of face recognition. However, face recognition skills are subject to wide individual variation, with some people showing exceptional ability-a group that has come to be known as 'super-recognisers'. The Metropolitan Police Force (London) recruits 'super-recognisers' from within its ranks, for deployment on various identification tasks. Here we test four working super-recognisers from within this police force, and ask whether they are really able to perform at levels above control groups. We consistently find that the police 'super-recognisers' perform at well above normal levels on tests of unfamiliar and familiar face matching, with degraded as well as high quality images. Recruiting employees with high levels of skill in these areas, and allocating them to relevant tasks, is an efficient way to overcome some of the known difficulties associated with unfamiliar face recognition.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Example trials from the Glasgow Face Matching Test (GFMT).

The top pair shows two instances of the same person, the bottom pair shows two different people. The individuals shown in Fig 1 have given written informed consent (as outlined in PLOS consent form) to publish these images.

Fig 2
Fig 2. Performance of police super-recognisers and comparison viewers.

Performance of super-recognisers (SR1–4; black) and comparison viewers (white) on three different tests of face recognition—the GFMT (left column), the MFMT (middle column), and the PLT (right column). Vertical lines indicate the range of scores for comparison groups, the deleted portion of the line shows the standard deviation, and the horizontal notch shows the mean. In all three tasks, chance performance is 50%.

Fig 3
Fig 3. Example trials from the PLT.

Images on the left show different identities (with the imposter face on the right). Images on the right show the same identity.

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References

    1. Burton AM, Wilson S, Cowan M, Bruce V. Face recognition in poor-quality video: Evidence from security surveillance. Psychol Sci. 1999;10(3):243–8.
    1. Lindsay RCL, Mansour JK, Kalmet N, Bertrand MI, Melsom L. Face perception and recognition in eyewitness memory In: Calder AJ, Rhodes G, Johnson MH, Haxby JV, Keane J. editors. The Oxford handbook of face perception. Oxford: Oxford University Press; 2011. pp. 307–328.
    1. Bruce V, Henderson Z, Greenwood K, Hancock PJB, Burton AM, Miller P. Verification of face identities from images captured on video. J Exp Psychol Appl. 1999;5(4):339–60.
    1. Bruce V, Henderson Z, Newman C, Burton AM. Matching identities of familiar and unfamiliar faces caught on CCTV images. J Exp Psychol Appl. 2001;7(3):207–18. - PubMed
    1. Burton AM, Jenkins R. Unfamiliar face perception In: Calder AJ, Rhodes G, Johnson MH, Haxby JV, Keane J. editors. Oxford Handbook of Face Perception. Oxford: Oxford University Press; 2011. pp. 287–306.

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Grants and funding

The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n.323262, and from the Economic and Social Research Council, UK (ES/J022950/1). http://erc.europa.eu/; http://www.esrc.ac.uk/. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.