Login / Signup

Low prevalence match and mismatch detection in simultaneous face matching: Influence of face recognition ability and feature focus guidance.

Josh P DavisCallan DrayNikolay PetrovElena Belanova
Published in: Attention, perception & psychophysics (2021)
Simultaneous face matching to verify identity is key to security and policing. However, matching is error-prone, particularly when target-item prevalence is low. Two experiments examined whether superior face recognition ability and the use of internal or external facial feature guidance scales would reduce low prevalence effects. In Experiment 1, super-recognisers (n = 317) significantly outperformed typical-ability controls (n = 452), while internal feature guidance enhanced accuracy across all prevalence conditions. However, an unexpected effect in controls revealed higher accuracy in low prevalence conditions, probably because no low-match or low-mismatch prevalence information was provided. In Experiment 2, top-end-of-typical range ability participants (n = 841) were informed of their low prevalence condition and demonstrated the expected low-prevalence effects. Findings and implications are discussed.
Keyphrases
  • risk factors
  • machine learning
  • deep learning
  • healthcare
  • public health
  • health information
  • label free