Dataset Information

Human-Computer Interaction in Face Matching.

ABSTRACT: 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.

SUBMITTER: Fysh MC

PROVIDER: S-EPMC6099365 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Human-Computer Interaction in Face Matching.

Fysh Matthew C MC Bindemann Markus M

Cognitive science 20180628

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 ...[more]

PMID: 29954047

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Project description:BackgroundMassively parallel genetic sequencing allows rapid testing of known intellectual disability (ID) genes. However, the discovery of novel syndromic ID genes requires molecular confirmation in at least a second or a cluster of individuals with an overlapping phenotype or similar facial gestalt. Using computer face-matching technology we report an automated approach to matching the faces of non-identical individuals with the same genetic syndrome within a database of 3681 images [1600 images of one of 10 genetic syndrome subgroups together with 2081 control images]. Using the leave-one-out method, two research questions were specified: 1) Using two-dimensional (2D) photographs of individuals with one of 10 genetic syndromes within a database of images, did the technology correctly identify more than expected by chance: i) a top match? ii) at least one match within the top five matches? or iii) at least one in the top 10 with an individual from the same syndrome subgroup? 2) Was there concordance between correct technology-based matches and whether two out of three clinical geneticists would have considered the diagnosis based on the image alone?ResultsThe computer face-matching technology correctly identifies a top match, at least one correct match in the top five and at least one in the top 10 more than expected by chance (P < 0.00001). There was low agreement between the technology and clinicians, with higher accuracy of the technology when results were discordant (P < 0.01) for all syndromes except Kabuki syndrome.ConclusionsAlthough the accuracy of the computer face-matching technology was tested on images of individuals with known syndromic forms of intellectual disability, the results of this pilot study illustrate the potential utility of face-matching technology within deep phenotyping platforms to facilitate the interpretation of DNA sequencing data for individuals who remain undiagnosed despite testing the known developmental disorder genes.

Project description:BackgroundInfants and children travel using passports that are typically valid for five years (e.g. Canada, United Kingdom, United States and Australia). These individuals may also need to be identified using images taken from videos and other sources in forensic situations including child exploitation cases. However, few researchers have examined how useful these images are as a means of identification.MethodsWe investigated the effectiveness of photo identification for infants and children using a face matching task, where participants were presented with two images simultaneously and asked whether the images depicted the same child or two different children. In Experiment 1, both images showed an infant (<1 year old), whereas in Experiment 2, one image again showed an infant but the second image of the child was taken at 4-5 years of age. In Experiments 3a and 3b, we asked participants to complete shortened versions of both these tasks (selecting the most difficult trials) as well as the short version Glasgow face matching test. Finally, in Experiment 4, we investigated whether information regarding the sex of the infants and children could be accurately perceived from the images.ResultsIn Experiment 1, we found low levels of performance (72% accuracy) for matching two infant photos. For Experiment 2, performance was lower still (64% accuracy) when infant and child images were presented, given the significant changes in appearance that occur over the first five years of life. In Experiments 3a and 3b, when participants completed both these tasks, as well as a measure of adult face matching ability, we found lowest performance for the two infant tasks, along with mixed evidence of within-person correlations in sensitivities across all three tasks. The use of only same-sex pairings on mismatch trials, in comparison with random pairings, had little effect on performance measures. In Experiment 4, accuracy when judging the sex of infants was at chance levels for one image set and above chance (although still low) for the other set. As expected, participants were able to judge the sex of children (aged 4-5) from their faces.DiscussionIdentity matching with infant and child images resulted in low levels of performance, which were significantly worse than for an adult face matching task. Taken together, the results of the experiments presented here provide evidence that child facial photographs are ineffective for use in real-world identification.

Dataset Information

Human-Computer Interaction in Face Matching.

Publications

Human-Computer Interaction in Face Matching.

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