The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Forensic confirmation bias: the case of facial image comparison
Abstract
Facial image comparison is the process of comparing a face with another (referred to as one-to-one facial image comparison or facial examination) or many others (one-to-many facial image comparison or facial review). As such it encompasses much of the basic visual cognition present in other forensic disciplines. The discipline has grown considerably since the introduction of facial recognition technology in the last decade (Spaun, 2007). Such technology is currently being used widely in the government and private sectors, including law enforcement (Phillips, 2011). Much like automated fingerprint identification systems (AFIS), the current generation of identification facial recognition systems require a human in the loop (Spaun, 2009). Research conducted over the past decade has consistently found that, although significant, the role of the human is often underestimated by organisations implementing facial recognition technology (O’Toole, Jiang, Roark, & Abdi, 2006; Spaun, 2009). This is not surprising, given that the importance of understanding the human role has often been overshadowed by the promises of the technology. As a consequence, the requirements for human-centered system design and training have often been neglected.
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Guidelines for training in facial comparison exist, but have not yet been subject to empirical validation.
“Whilst guidelines for training in facial comparison do exist [19, 39, 40], these have not yet been subject to empirical validation.”
From Error Rates in Users of Automatic Face Recognition Software (2015) · cites this paper as [40]
Citations
Cites
How we see ourselves and how we see others
Pronin, E. (2008) · Science · doi:10.1126/science.1154199 · Cited by 353
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Research works printed but not linked: 13
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- Kassin, 2013, The forensic confirmation bias: Problems, perspectives and proposed solutions, Journal of Applied Research in Memory and Cognition, 2, 42, 10.1016/j.jarmac.2013.01.001 · DOI · Paper page
- Mallett, 2010, An exploration of sample representativeness in anthropometric facial comparison, Journal of Forensic Sciences, 55, 1025, 10.1111/j.1556-4029.2010.01425.x · DOI
- Megreya, 2006, Unfamiliar faces are not faces: Evidence from a matching task, Memory and Cognition, 34, 865, 10.3758/BF03193433 · DOI · Paper page
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Cited by
Sorted by citations
Error Rates in Users of Automatic Face Recognition Software
White, D., Dunn, J. D., Schmid, A. C., & Kemp, R. I. (2015) · PLOS ONE · doi:10.1371/journal.pone.0139827 · Cited by 141
Validation of forensic facial comparison by morphological analysis in photographic and CCTV samples
Bacci, N., Houlton, T. M. R., Briers, N., & Steyn, M. (2021) · International Journal of Legal Medicine · doi:10.1007/s00414-021-02512-3 · Cited by 23
Finding Makhubu: A morphological forensic facial comparison
Houlton, T. M. R., & Steyn, M. (2018) · Forensic Science International · doi:10.1016/j.forsciint.2018.01.022 · Cited by 13
Metadata
- Authors
- Heyer, R., & Semmler, C.
- Venue
- Journal of Applied Research in Memory and Cognition
- Published
- 2013-03
- Volume
- 2
- Issue
- 1
- Pages
- 68-70
- ISSN
- 2211-369X
- 2211-3681
- Cited by
- 15
- References
- 1
- Language
- en
- Funders
- Department of Prime Minister
- Research Support for National Security Program (PR09-0078)
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