The rapid development in the field of computer graphics (CG) makes it quite easy to create photo-realistic images and videos. This brings forward an emergent requirement for techniques that can distinguish CG from real contents. In this paper, we propose a method that leverages human pulse signal to distinguish between CG and real videos that include human faces. We use a robust tracking method to locate a patch of skin on the face. Then, a chrominance-based algorithm is employed to robustly extract pulse signal. By checking the frequency waveform of the extracted pulse signal, we can tell CG and real videos apart. The experiment shows encouraging results, which demonstrate the efficiency of our method.