Face Identification within Realistic Contexts, 2019-2022

DOI

In many situations, security relies on accurate person identification. At airports, routine person identifications are based on face matching, in which passport officers have to decide whether the face photograph in a presented identity document actually depicts its bearer. This project investigated these person identifications by examining face matching with laboratory paradigms and in virtual reality. Data from a series of studies is provided that describe how to build and validate person avatars for such experimentation in VR and examine the role of different factors in face matching (similarity; moles; mismatch frequency; distractions).In many situations, security relies on accurate person identification. At airports, routine person identifications are based on face matching, in which passport officers have to decide whether the face photograph in a presented identity document actually depicts its bearer. This project investigated these person identifications by examining face matching with laboratory paradigms and in virtual reality. Data from a series of studies is provided that describe how to build and validate person avatars for such experimentation in VR and examine the role of different factors in face matching (similarity; moles; mismatch frequency; distractions).

Cognitive Psychology experiments in the laboratory and online, measuring identification responses to faces and passport photographs. Participants were volunteers from the general population and student population, who provided informed consent to take part.

Identifier
DOI https://doi.org/10.5255/UKDA-SN-855832
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=d1d9d80c5e97d0c0d4b34e1b5c14c24ebd5a8dbd7507409820ee0f64ab7aad6d
Provenance
Creator Bindemann, M, University of Kent; Burton, M, University of York; McCall, C, University of York
Publisher UK Data Service
Publication Year 2022
Funding Reference Economic and Social Research Council
Rights Markus Bindemann, University of Kent; The Data Collection is available to any user without the requirement for registration for download/access.
OpenAccess true
Representation
Resource Type Numeric
Discipline Psychology; Social and Behavioural Sciences
Spatial Coverage United Kingdom