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Diagnostic feature training improves face matching accuracy.

Alice Towler1, Michelle Keshwa1, Bianca Ton1

  • 1School of Psychology.

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|April 29, 2021
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Training novices to focus on diagnostic facial features like ears and marks significantly improves unfamiliar face matching accuracy by 6%. This brief training method enhances performance, approaching expert-level ability in just six minutes.

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Area of Science:

  • Cognitive Psychology
  • Forensic Science
  • Perceptual Learning

Background:

  • Unfamiliar face identification is prone to errors, even for professionals.
  • Previous training methods for face recognition have largely failed.
  • Face identity processing is often considered difficult to improve through perceptual learning.

Purpose of the Study:

  • To develop and evaluate a novel training approach for unfamiliar face matching.
  • To investigate the effectiveness of expert-derived feature-based strategies.
  • To determine if perceptual learning can enhance face identification accuracy.

Main Methods:

  • Employed an expert knowledge elicitation approach to identify diagnostic facial features.
  • Trained novices to focus on specific features (ears, facial marks) identified by experts.
  • Compared accuracy on unfamiliar face matching tasks before and after training.

Main Results:

  • A 6-minute training intervention focusing on diagnostic features improved face matching accuracy by 6%.
  • This training accounted for roughly half of the performance gap between novices and experts.
  • Training benefits were contingent on the visibility of diagnostic features.

Conclusions:

  • Expert-derived feature-based training is a promising method for improving unfamiliar face matching.
  • Focusing on diagnostically important but often undervalued features can enhance performance.
  • This data-driven approach offers an alternative to theory-driven training for face recognition tasks.