Masked face matching benefits from isolated facial features - Mengying Zhang; Melanie Sauerland; Anna Sagana (PLoS ONE, 2025)
Verifying the identity of an unfamiliar person is a difficult task, especially when targets wear masks that cover most of their faces. This presents a major challenge for law enforcement in border control, security, and criminal investigations. Therefore, we aim to explore ways to improve face-matching performance when a face is heavily masked. In two experiments, we investigated whether face-matching performance can benefit from the presentation of isolated facial features, namely the eyes (Experiment 1) and the mouth (Experiment 2), when a target face is masked. Participants viewed pairs of faces and determined whether they belonged to the same person or different people. In congruent pairs, participants matched a full-face image to another full-face image or a masked image to an isolated facial feature. In incongruent pairs, participants matched a full-face image to an image of the eyes or the mouth only or to a masked image. Matching accuracy was significantly better in congruent than incongruent pairs. Interestingly, the benefit of showing an isolated facial feature was even present when that single feature was the mouth. Overall, the findings showed that focusing on isolated facial features, such as the eyes or mouth, can be a valuable strategy for enhancing identity matching with masked perpetrators.