Literature DB >> 25537273

The effect of image quality and forensic expertise in facial image comparisons.

Kristin Norell1, Klas Brorsson Läthén, Peter Bergström, Allyson Rice, Vaidehi Natu, Alice O'Toole.   

Abstract

Images of perpetrators in surveillance video footage are often used as evidence in court. In this study, identification accuracy was compared for forensic experts and untrained persons in facial image comparisons as well as the impact of image quality. Participants viewed thirty image pairs and were asked to rate the level of support garnered from their observations for concluding whether or not the two images showed the same person. Forensic experts reached their conclusions with significantly fewer errors than did untrained participants. They were also better than novices at determining when two high-quality images depicted the same person. Notably, lower image quality led to more careful conclusions by experts, but not for untrained participants. In summary, the untrained participants had more false negatives and false positives than experts, which in the latter case could lead to a higher risk of an innocent person being convicted for an untrained witness.
© 2014 American Academy of Forensic Sciences.

Entities:  

Keywords:  CCTV; biometric identification; facial image comparison; forensic science; image quality; information science

Mesh:

Year:  2014        PMID: 25537273     DOI: 10.1111/1556-4029.12660

Source DB:  PubMed          Journal:  J Forensic Sci        ISSN: 0022-1198            Impact factor:   1.832


  9 in total

1.  Perceptual expertise in forensic facial image comparison.

Authors:  David White; P Jonathon Phillips; Carina A Hahn; Matthew Hill; Alice J O'Toole
Journal:  Proc Biol Sci       Date:  2015-09-07       Impact factor: 5.349

2.  Error Rates in Users of Automatic Face Recognition Software.

Authors:  David White; James D Dunn; Alexandra C Schmid; Richard I Kemp
Journal:  PLoS One       Date:  2015-10-14       Impact factor: 3.240

3.  Face Recognition by Metropolitan Police Super-Recognisers.

Authors:  David J Robertson; Eilidh Noyes; Andrew J Dowsett; Rob Jenkins; A Mike Burton
Journal:  PLoS One       Date:  2016-02-26       Impact factor: 3.240

4.  Improving face identification with specialist teams.

Authors:  Tarryn Balsdon; Stephanie Summersby; Richard I Kemp; David White
Journal:  Cogn Res Princ Implic       Date:  2018-06-27

5.  Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms.

Authors:  P Jonathon Phillips; Amy N Yates; Ying Hu; Carina A Hahn; Eilidh Noyes; Kelsey Jackson; Jacqueline G Cavazos; Géraldine Jeckeln; Rajeev Ranjan; Swami Sankaranarayanan; Jun-Cheng Chen; Carlos D Castillo; Rama Chellappa; David White; Alice J O'Toole
Journal:  Proc Natl Acad Sci U S A       Date:  2018-05-29       Impact factor: 11.205

6.  Do professional facial image comparison training courses work?

Authors:  Alice Towler; Richard I Kemp; A Mike Burton; James D Dunn; Tanya Wayne; Reuben Moreton; David White
Journal:  PLoS One       Date:  2019-02-13       Impact factor: 3.240

7.  3D-3D facial registration method applied to personal identification: Does it work with limited portions of faces? An experiment in ideal conditions.

Authors:  Daniele Gibelli; Andrea Palamenghi; Pasquale Poppa; Chiarella Sforza; Cristina Cattaneo; Danilo De Angelis
Journal:  J Forensic Sci       Date:  2022-02-28       Impact factor: 1.717

8.  Solving the Border Control Problem: Evidence of Enhanced Face Matching in Individuals with Extraordinary Face Recognition Skills.

Authors:  Anna Katarzyna Bobak; Andrew James Dowsett; Sarah Bate
Journal:  PLoS One       Date:  2016-02-01       Impact factor: 3.240

Review 9.  Forensic Facial Comparison: Current Status, Limitations, and Future Directions.

Authors:  Nicholas Bacci; Joshua G Davimes; Maryna Steyn; Nanette Briers
Journal:  Biology (Basel)       Date:  2021-12-03
  9 in total

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