Literature DB >> 26336174

Perceptual expertise in forensic facial image comparison.

David White1, P Jonathon Phillips2, Carina A Hahn3, Matthew Hill3, Alice J O'Toole3.   

Abstract

Forensic facial identification examiners are required to match the identity of faces in images that vary substantially, owing to changes in viewing conditions and in a person's appearance. These identifications affect the course and outcome of criminal investigations and convictions. Despite calls for research on sources of human error in forensic examination, existing scientific knowledge of face matching accuracy is based, almost exclusively, on people without formal training. Here, we administered three challenging face matching tests to a group of forensic examiners with many years' experience of comparing face images for law enforcement and government agencies. Examiners outperformed untrained participants and computer algorithms, thereby providing the first evidence that these examiners are experts at this task. Notably, computationally fusing responses of multiple experts produced near-perfect performance. Results also revealed qualitative differences between expert and non-expert performance. First, examiners' superiority was greatest at longer exposure durations, suggestive of more entailed comparison in forensic examiners. Second, experts were less impaired by image inversion than non-expert students, contrasting with face memory studies that show larger face inversion effects in high performers. We conclude that expertise in matching identity across unfamiliar face images is supported by processes that differ qualitatively from those supporting memory for individual faces.
© 2015 The Author(s).

Entities:  

Keywords:  biometrics; face recognition; forensic science; person identification; visual expertise

Mesh:

Year:  2015        PMID: 26336174      PMCID: PMC4571699          DOI: 10.1098/rspb.2015.1292

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


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Review 6.  Visual search in scenes involves selective and nonselective pathways.

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7.  Fusing face-verification algorithms and humans.

Authors:  Alice J O'Toole; Hervé Abdi; Fang Jiang; P Jonathon Phillips
Journal:  IEEE Trans Syst Man Cybern B Cybern       Date:  2007-10

8.  The effect of image quality and forensic expertise in facial image comparisons.

Authors:  Kristin Norell; Klas Brorsson Läthén; Peter Bergström; Allyson Rice; Vaidehi Natu; Alice O'Toole
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9.  The nature of expertise in fingerprint matching: experts can do a lot with a little.

Authors:  Matthew B Thompson; Jason M Tangen
Journal:  PLoS One       Date:  2014-12-17       Impact factor: 3.240

10.  Passport officers' errors in face matching.

Authors:  David White; Richard I Kemp; Rob Jenkins; Michael Matheson; A Mike Burton
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3.  Error Rates in Users of Automatic Face Recognition Software.

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5.  Face Recognition by Metropolitan Police Super-Recognisers.

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6.  Feature-by-feature comparison and holistic processing in unfamiliar face matching.

Authors:  Ahmed M Megreya
Journal:  PeerJ       Date:  2018-02-26       Impact factor: 2.984

7.  Effects of time pressure and time passage on face-matching accuracy.

Authors:  Matthew C Fysh; Markus Bindemann
Journal:  R Soc Open Sci       Date:  2017-06-07       Impact factor: 2.963

8.  Improving face identification with specialist teams.

Authors:  Tarryn Balsdon; Stephanie Summersby; Richard I Kemp; David White
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9.  Solving the Border Control Problem: Evidence of Enhanced Face Matching in Individuals with Extraordinary Face Recognition Skills.

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Journal:  PLoS One       Date:  2016-02-01       Impact factor: 3.240

10.  Matching Faces Against the Clock.

Authors:  Markus Bindemann; Matthew Fysh; Katie Cross; Rebecca Watts
Journal:  Iperception       Date:  2016-10-03
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