Literature DB >> 21198254

Finding needles in haystacks: identity mismatch frequency and facial identity verification.

Markus Bindemann1, Meri Avetisyan, Kristy-Ann Blackwell.   

Abstract

Accurate person identification is central to all security, police, and judicial systems. A commonplace method to achieve this is to compare a photo-ID and the face of its purported owner. The critical aspect of this task is to spot cases in which these two instances of a face do not match. Studies of person identification show that these instances often go undetected when mismatches occur regularly in an experiment, but this differs from everyday operations in which identity mismatches are rare. The current study therefore examined whether infrequent identity mismatches are more likely to go undetected by observers. In Experiments 1 and 2, identity mismatches were detected equally under low (2%) and high (50%) mismatch prevalence. This pattern persisted when viewing conditions were optimized for person identification in Experiment 3, by using a card-sorting task in which all face identities could be viewed repeatedly, and also under increased task difficulty, by constraining viewing conditions temporally in Experiment 4. These results imply that the infrequent occurrence of identity mismatches in security settings such as passport control does not impair an observer's ability to detect these important events. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

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Year:  2010        PMID: 21198254     DOI: 10.1037/a0021893

Source DB:  PubMed          Journal:  J Exp Psychol Appl        ISSN: 1076-898X


  8 in total

1.  Infrequent identity mismatches are frequently undetected.

Authors:  Megan H Papesh; Stephen D Goldinger
Journal:  Atten Percept Psychophys       Date:  2014-07       Impact factor: 2.199

2.  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

3.  Human-Computer Interaction in Face Matching.

Authors:  Matthew C Fysh; Markus Bindemann
Journal:  Cogn Sci       Date:  2018-06-28

4.  You shall not pass: how facial variability and feedback affect the detection of low-prevalence fake IDs.

Authors:  Dawn R Weatherford; William Blake Erickson; Jasmyne Thomas; Mary E Walker; Barret Schein
Journal:  Cogn Res Princ Implic       Date:  2020-01-28

5.  Prior experience with target encounter affects attention allocation and prospective memory performance.

Authors:  Kara N Moore; James Michael Lampinen; Eryn J Adams; Blake L Nesmith; Presley Burch
Journal:  Cogn Res Princ Implic       Date:  2022-05-07

6.  The low prevalence effect in fingerprint comparison amongst forensic science trainees and novices.

Authors:  Bethany Growns; James D Dunn; Rebecca K Helm; Alice Towler; Jeff Kukucka
Journal:  PLoS One       Date:  2022-08-11       Impact factor: 3.752

7.  Feature instructions improve face-matching accuracy.

Authors:  Ahmed M Megreya; Markus Bindemann
Journal:  PLoS One       Date:  2018-03-15       Impact factor: 3.240

8.  Photo ID verification remains challenging despite years of practice.

Authors:  Megan H Papesh
Journal:  Cogn Res Princ Implic       Date:  2018-06-27
  8 in total

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