Investigating idiosyncratic facial dynamics with motion retargeting

3D facial animation systems allow the creation of well-controlled stimuli to study face processing. Despite this high level of control, such stimuli often lack naturalness due to artificial facial dynamics (eg linear morphing). The present study investigates the extent to which human visual perception can be fooled by artificial facial motion. We used a system that decomposes facial motion capture data into time courses of basic action shapes (Curio et al, 2006 APGV 1 77–84). Motion capture data from four short facial expressions were input to the system. The resulting time courses and five approximations were retargeted onto a 3D avatar head using basic action shapes created manually in Poser. Sensitivity to the subtle modifications was measured in a matching task using video sequences of the actor performing the corresponding expressions as target. Participants were able to identify the unmodified retargeted facial motion above chance level under all conditions. Furthermore, matching performance for the different approximations varied with expression. Our findings highlight the sensitivity of human perception for subtle facial dynamics. Moreover, the action shape-based system will allow us to further investigate the perception of idiosyncratic facial motion using well-controlled facial animation stimuli