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Human–Computer Interaction in Face Matching

Automatic facial recognition is becoming increasingly ubiquitous in security contexts such as passport control. Currently, Automated Border Crossing (ABC) systems in the United Kingdom (UK) and the European Union (EU) require supervision from a human operator who validates correct identity judgments...

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Detalles Bibliográficos
Autores principales: Fysh, Matthew C., Bindemann, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6099365/
https://www.ncbi.nlm.nih.gov/pubmed/29954047
http://dx.doi.org/10.1111/cogs.12633
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author Fysh, Matthew C.
Bindemann, Markus
author_facet Fysh, Matthew C.
Bindemann, Markus
author_sort Fysh, Matthew C.
collection PubMed
description Automatic facial recognition is becoming increasingly ubiquitous in security contexts such as passport control. Currently, Automated Border Crossing (ABC) systems in the United Kingdom (UK) and the European Union (EU) require supervision from a human operator who validates correct identity judgments and overrules incorrect decisions. As the accuracy of this human–computer interaction remains unknown, this research investigated how human validation is impacted by a priori face‐matching decisions such as those made by automated face recognition software. Observers matched pairs of faces that were already labeled onscreen as depicting the same identity or two different identities. The majority of these labels provided information that was consistent with the stimuli presented, but some were also inconsistent or provided “unresolved” information. Across three experiments, accuracy consistently deteriorated on trials that were inconsistently labeled, indicating that observers’ face‐matching decisions are biased by external information such as that provided by ABCs.
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spelling pubmed-60993652018-08-24 Human–Computer Interaction in Face Matching Fysh, Matthew C. Bindemann, Markus Cogn Sci Brief Reports Automatic facial recognition is becoming increasingly ubiquitous in security contexts such as passport control. Currently, Automated Border Crossing (ABC) systems in the United Kingdom (UK) and the European Union (EU) require supervision from a human operator who validates correct identity judgments and overrules incorrect decisions. As the accuracy of this human–computer interaction remains unknown, this research investigated how human validation is impacted by a priori face‐matching decisions such as those made by automated face recognition software. Observers matched pairs of faces that were already labeled onscreen as depicting the same identity or two different identities. The majority of these labels provided information that was consistent with the stimuli presented, but some were also inconsistent or provided “unresolved” information. Across three experiments, accuracy consistently deteriorated on trials that were inconsistently labeled, indicating that observers’ face‐matching decisions are biased by external information such as that provided by ABCs. John Wiley and Sons Inc. 2018-06-28 2018-07 /pmc/articles/PMC6099365/ /pubmed/29954047 http://dx.doi.org/10.1111/cogs.12633 Text en © 2018 The Authors. Cognitive Science ‐ A Multidisciplinary Journal published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society (CSS). This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Brief Reports
Fysh, Matthew C.
Bindemann, Markus
Human–Computer Interaction in Face Matching
title Human–Computer Interaction in Face Matching
title_full Human–Computer Interaction in Face Matching
title_fullStr Human–Computer Interaction in Face Matching
title_full_unstemmed Human–Computer Interaction in Face Matching
title_short Human–Computer Interaction in Face Matching
title_sort human–computer interaction in face matching
topic Brief Reports
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6099365/
https://www.ncbi.nlm.nih.gov/pubmed/29954047
http://dx.doi.org/10.1111/cogs.12633
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