Within-person variability can improve the identification of unfamiliar faces across changes in viewpoint

Unfamiliar face identification is concerningly error prone, especially across changes in viewing conditions. Within-person variability has been shown to improve matching performance for unfamiliar faces, but this has only been demonstrated using images of a front view. In this study, we test whether the advantage of within-person variability from front views extends to matching to target images of a face rotated in view. Participants completed either a simultaneous matching task (Experiment 1) or a sequential matching task (Experiment 2) in which they were tested on their ability to match the identity of a face shown in an array of either one or three ambient front-view images, with a target image shown in front, three-quarter, or profile view. While the effect was stronger in Experiment 2, we found a consistent pattern in match trials across both experiments in that there was a multiple image matching benefit for front, three-quarter, and profile-view targets. We found multiple image effects for match trials only, indicating that providing observers with multiple ambient images confers an advantage for recognising different images of the same identity but not for discriminating between images of different identities. Signal detection measures also indicate a multiple image advantage despite a more liberal response bias for multiple image trials. Our results show that within-person variability information for unfamiliar faces can be generalised across views and can provide insights into the initial processes involved in the representation of familiar faces.