Dissociating identity from gait: A virtual reality study of the role of dynamic identity signatures in person recognition

Studies on person recognition have primarily examined recognition of static faces, presented on a computer screen at a close distance. Nevertheless, in naturalistic situations we typically see the whole dynamic person, often approaching from a distance. In such cases, facial information may be less clear, and the motion pattern of an individual, their dynamic identity signature (DIS), may be used for person recognition. Recently, several studies examined the role of motion in person recognition by presenting videos of people in motion. However, such stimuli do not allow for the dissociation of gait from identity, as different individuals differ both in their gait and their identity. To examine the role of gait independently from person identity in person recognition, we used a virtual environment, which enables presenting the same type of gait across different identities. Using this setting, we assessed the accuracy and distance at which identities are recognized based on their gait, as a function of gait distinctiveness. Furthermore, the virtual environment also enabled us to assess, for the first time, the distance at which a person is recognized as a continuous variable. We find that the accuracy and distance at which people were recognized increased with gait distinctiveness. Importantly, these effects were found when recognizing identities in motion but not from static displays, indicating that DIS rather than attention, enabled more accurate person recognition. Overall these findings highlight an important role for gait in real-life person recognition and stress that gait contributes to recognition independently from the face and body.