CoChat
Sign Up
Cited by 33

The DOI matches its Crossref record.

Are facial image analysis experts any better than the general public at identifying individuals from CCTV images?

Wilkinson, Caroline, Evans, Raymond·2009·Science & Justice
DOI 10.1016/j.scijus.2008.10.011
Open this paper in CoChat — free account

Abstract

The aim of this study was to examine the accuracy and reliability of a small group of facial imagery experts, and compare their abilities with members of the general public, to ascertain whether or not training and experience will affect the ability to identify faces from CCTV footage. A number of clips from CCTV footage were utilised alongside face pools. The participants were asked to identify the actor in each CCTV clip and provide a level of confidence in the decision. The experts tested in this study were consistently better at identification than the public, with almost double the identification rates and half the errors. These results suggest that training and experience in facial analysis will produce more reliable and accurate facial identification.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.scijus.2008.10.011

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Experts perform notably better than members of the public at facial comparison, even when image quality is taken into consideration.

    “Experts, in fact, perform notably better than members of the public [42], even when image quality was taken into consideration [132].”

    From Forensic Facial Comparison: Current Status, Limitations, and Future Directions (2021) · cites this paper as [42]

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 14

  1. Henderson, 2001, Matching the faces of robbers captured on video, Applied Cognitive Psychology, 15, 445, 10.1002/acp.718 · DOI · Paper page
  2. Davies, 2000, Closed-circuit television: how effective an identification aid?, British Journal of Psychology, 91, 411, 10.1348/000712600161907 · DOI
  3. Bruce, 2001, Matching identities of familiar and unfamiliar faces caught on CCTV images, Journal of Experimental Psychology. Applied, 7, 207, 10.1037/1076-898X.7.3.207 · DOI · Paper page
  4. Keval, 2008, Can we ID from CCTV?, vol. 6982
  5. Burton, 1999, Face recognition in poor-quality video, Psychological Science, 10, 243, 10.1111/1467-9280.00144 · DOI · Paper page
  6. Halberstein, 2001, The application of anthropometric indices in forensic photography; three case studies, Journal of Forest Science, 46, 1438
  7. Porter, 1998, The application of forensic photography for facial identification methods, Imaging Science Journal, 46, 175
  8. Porter, 2000, An anatomical and photographic technique for forensic facial identification, Forest Science-International, 114, 97, 10.1016/S0379-0738(00)00290-5 · DOI
  9. Catterick, 1992, Facial measurements as an aid to recognition, Forest Science-International, 56, 23, 10.1016/0379-0738(92)90142-J · DOI
  10. Mardia, 1996, On statistical problems with face identification from photographs, Journal of Applied Statistics, 23, 655, 10.1080/02664769624008 · DOI
  11. Kleinberg, 2007, Failure of anthropometry as a facial identification technique using high-quality photographs, Journal of Forensic Sciences, 52, 779, 10.1111/j.1556-4029.2007.00458.x · DOI · Paper page
  12. Ellis, 1979, Identification of familiar and unfamiliar faces from internal and external features: some implications for theories of face recognition, Perception, 8, 431, 10.1068/p080431 · DOI
  13. I.N. Jarudi and P. Sinha. Relative contributions of internal and external features to face recognition. A1 Memo 2003 Massachusetts Institute of Technology – Artificial Intelligence laboratory. · DOI
  14. Dror, 2008, Meta-analytically quantifying the reliability and biasability of forensic experts, Journal of Forensic Sciences, 53, 900, 10.1111/j.1556-4029.2008.00762.x · DOI

Cited by

Sorted by citations

Metadata

Authors
Wilkinson, C., & Evans, R.
Venue
Science & Justice
Publisher
Elsevier BV
Published
2009-09
Volume
49
Issue
3
Pages
191-196
ISSN
1355-0306
DOI
10.1016/j.scijus.2008.10.011
Cited by
33
References
0
Language
en
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review