Identity in the Spotlight: Matching Faces Without Overlapping Features

One-to-one face matching is widely used for identity verification yet becomes difficult with unfamiliar faces or when parts of the face are covered. We investigated whether observers could accurately verify identity from different non-overlapping facial fragments. Each stimulus of our novel face matching task had the appearance of a single face image as revealed through four circular ‘spotlights,’ one from each quadrant of the face. Observers judged whether the designated target spotlight (from image A) depicted the same identity as the three reference spotlights sampled from a different image (all from image B). Across three experiments, we examined observers’ matching performance for familiar and unfamiliar faces under Baseline (Experiment 1), Scrambled (Experiment 2), and Inverted (Experiment 3) spotlight arrangements. Observers’ accuracy reliably exceeded chance (proportion correct: 0.53–0.59), except when the faces were familiar and inverted. Accuracy was higher for familiar faces when the spotlights were presented in an upright orientation, but scrambling their spatial location and inverting them reversed this familiar face advantage. Notably, accuracy with the unfamiliar face spotlights significantly improved with inversion. These findings show that observers can make use of latent visual information distributed across different images and regions of the face to distinguish identities.