We know from previous research that unfamiliar face matching (determining whether two simultaneously presented images show the same person or not) is very error-prone. A small number of studies in laboratory settings have shown that the use of multiple images or a face average, rather than a single image, can improve face matching performance. Here, we tested 1,999 participants using four-image arrays and face averages in two separate live matching tasks. Matching a single image to a live person resulted in numerous errors (79.9% accuracy across both experiments), and neither multiple images (82.4% accuracy) nor face averages (76.9% accuracy) improved performance. These results are important when considering possible alterations which could be made to photo-ID. Although multiple images and face averages have produced measurable improvements in performance in recent laboratory studies, they do not produce benefits in a real-world live face matching context.
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