Investigating the impact of motion visual synchrony on self face recognition using real time morphing.

Face recognition is a crucial aspect of self-image and social interactions. Previous studies have focused on static images to explore the boundary of self-face recognition. Our research, however, investigates the dynamics of face recognition in contexts involving motor-visual synchrony. We first validated our morphing face metrics for self-face recognition. We then conducted an experiment using state-of-the-art video processing techniques for real-time face identity morphing during facial movement. We examined self-face recognition boundaries under three conditions: synchronous, asynchronous, and static facial movements. Our findings revealed that participants recognized a narrower self-face boundary with moving facial images compared to static ones, with no significant differences between synchronous and asynchronous movements. The direction of morphing consistently biased the recognized self-face boundary. These results suggest that while motor information of the face is vital for self-face recognition, it does not rely on movement synchronization, and the sense of agency over facial movements does not affect facial identity judgment. Our methodology offers a new approach to exploring the 'self-face boundary in action', allowing for an independent examination of motion and identity.