Creating facial animations that convey an animator’s intent is a difficult task because animation techniques are necessarily an approximation of the subtle motion of the face. Some animation techniques may result in linearization of the motion of vertices in space (blendshapes, for example), and other, simpler techniques may result in linearization of the motion in time. In this article, we consider the problem of animating smiles and explore how these simplifications in space and time affect the perceived genuineness of smiles. We create realistic animations of spontaneous and posed smiles from high-resolution motion capture data for two computer-generated characters. The motion capture data is processed to linearize the spatial or temporal properties of the original animation. Through perceptual experiments, we evaluate the genuineness of the resulting smiles. Both space and time impact the perceived genuineness. We also investigate the effect of head motion in the perception of smiles and show similar results for the impact of linearization on animations with and without head motion. Our results indicate that spontaneous smiles are more heavily affected by linearizing the spatial and temporal properties than posed smiles. Moreover, the spontaneous smiles were more affected by temporal linearization than spatial linearization. Our results are in accordance with previous research on linearities in facial animation and allow us to conclude that a model of smiles must include a nonlinear model of velocities.