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Evaluating the feature comparison strategy for forensic face identification.
Abstract
Face recognition is thought to rely on representations that encode holistic properties. Paradoxically, professional forensic examiners who identify unfamiliar faces by comparing facial images are trained to adopt a feature-by-feature comparison strategy. Here we tested the effectiveness of this strategy by asking participants to rate facial feature similarity prior to making same/different identity decisions to pairs of face images. Experiment 1 provided preliminary evidence that rating feature similarity improves unfamiliar face matching accuracy in novice participants. In Experiment 2, we found benefits of this procedure over and above rating similarity of personality traits and image quality parameters, suggesting that benefits are not solely attributable to general increases in attention. In Experiment 3, we then compared performance of trained forensic facial image examiners to novice participants, and found that examiners displayed: i) superior face matching accuracy; ii) smaller face inversion and feature inversion effects; and iii) feature ratings that were more diagnostic of identity. Further, aggregating feature ratings of multiple examiners produced perfect identity discrimination. Based on these quantitative and qualitative differences between experts and novices, we conclude that comparison based on local features confers specific benefits to trained forensic examiners. (PsycINFO Database Record
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Facial examiners-who receive extensive training in feature comparison-tend to outperform novices.
“It is also consistent with the fact that facial examiners—who receive extensive training in feature comparison—tend to outperform novices (e.g., [20, 22–24]).”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
In previous work, examiners' accuracy was less impaired when face images were presented upside down compared to novices.
“and their accuracy was less impaired when face images were presented upside down compared to novices [20, 22].”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
Facial examiners show qualitative differences in performance: extracting more diagnostic identity information from facial features than novices.
“Importantly, these experts also show qualitative differences in their performance: extracting more diagnostic identity information from facial features than novices [20], and showing smaller face inversion effects [20, 22] (see S3 Appendix for details of the inversion effect).”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
The accuracy improvements observed in Course D are consistent with previous work showing that feature-by-feature comparison improves face identification accuracy in novices.
“The accuracy improvements observed in Course D are consistent with previous work showing that feature-by-feature comparison improves face identification accuracy in novices [20].”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
Recent studies show that facial examiners are more accurate than novices on face identification tasks.
“Recent studies show that facial examiners are more accurate than novices on face identification tasks [20, 22–24].”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
The superior accuracy experienced by facial examiners is typically accompanied by qualitative differences in their performance.
“However, the superior accuracy experienced by facial examiners is typically accompanied by qualitative differences in their performance.”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
Course D did not produce the qualitative changes associated with expertise in facial image comparison: increased diagnosticity of facial feature similarity ratings and a reduced inversion effect.
“In addition, Course D did not produce the qualitative changes associated with expertise in facial image comparison: increased diagnosticity of facial feature similarity ratings and a reduced inversion effect [20, 22].”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
Facial examiners are a specialist group of facial image comparison practitioners who conduct slow, systematic, feature-based comparisons, often as part of criminal investigations.
“Facial examiners are a specialist group of facial image comparison practitioners who conduct slow, systematic, feature-based comparisons, often as part of criminal investigations (see [20, 22, 23]).”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
In previous work, examiners' ratings of facial feature similarity were more diagnostic of identity.
“In previous work, examiners’ ratings of facial feature similarity were more diagnostic of identity [20]”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
Course D is the only reviewed course to cite empirical evidence to support some of the training material.
“Only two courses (J and K) include reference to scientific studies of error-rates in novice and/or professional groups, and Course D is the only course to cite empirical evidence to support some of the training material [20].”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
Facial examiners show smaller face inversion effects than novices.
“Importantly, these experts also show qualitative differences in their performance: extracting more diagnostic identity information from facial features than novices [20], and showing smaller face inversion effects [20, 22] (see S3 Appendix for details of the inversion effect).”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
These possibilities do not account for the qualitative differences observed in their performance in previous work.
“However, these possibilities do not account for the qualitative differences observed in their performance in previous work [20, 22].”
From Do professional facial image comparison training courses work? (2019) · cites this paper as [20]
Citations
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Sorted by citations
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Phillips, P. J., Hahn, C. A., Fontana, P. C., Yates, A. N., Greene, K., Broniatowski, D. A., & Przybocki, M. A. (2021) · doi:10.6028/nist.ir.8312 · Cited by 262
Young, A. W., & Burton, A. M. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.11.007 · Cited by 235
Four Principles of Explainable Artificial Intelligence
Phillips, P. J., Hahn, C. A., Fontana, P. C., Broniatowski, D. A., & Przybocki, M. A. (2020) · doi:10.6028/nist.ir.8312-draft · Cited by 136
Do professional facial image comparison training courses work?
Towler, A., Kemp, R. I., Burton, A. M., Dunn, J. D., Wayne, T., Moreton, R., & White, D. (2019) · PLOS ONE · doi:10.1371/journal.pone.0211037 · Cited by 111
Self-citationThinking forensics: Cognitive science for forensic practitioners
Edmond, G., Towler, A., Growns, B., Ribeiro, G., Found, B., White, D., Ballantyne, K., Searston, R. A., Thompson, M. B., Tangen, J. M., et al. (2017) · Science & Justice · doi:10.1016/j.scijus.2016.11.005 · Cited by 95
Self-citationForensic Facial Comparison: Current Status, Limitations, and Future Directions
Bacci, N., Davimes, J. G., Steyn, M., & Briers, N. (2021) · Biology · doi:10.3390/biology10121269 · Cited by 26
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
Growns, B., & Kukucka, J. (2021) · Applied Cognitive Psychology · doi:10.1002/acp.3800 · Cited by 20
Metadata
- Authors
- Towler, A., White, D., & Kemp, R. I.
- ORCID
- Towler, Alice
- Venue
- Journal of Experimental Psychology: Applied
- Published
- 2017
- Volume
- 23
- Issue
- 1
- Pages
- 47-58
- ISSN
- 1939-2192
- 1076-898X
- Cited by
- 58
- References
- 0
- Language
- en
- Funders
- Australian Research Council (LP110100448, LP 130100702)
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