Single 2D Image-based 3D Face Reconstruction and Its Application in Pose Estimation

Abstract

Human beings are born with a natural capacity of recovering shape from merely one image. However, it is still a challenging mission for current techniques to make a computer have such an ability. To simulate the modeling procedure of human visual system, a Ternary Deformation Framework (TDF) is proposed to reconstruct a realistic 3D face from one 2D frontal facial image, with prior knowledge regarding facial shape learnt from a 3D face data set. Based upon the reconstructed 3D face, a novelmethod via linear regression is then proposed to estimate that person's pose on another image with pose variations. Simulation results show that TDF outperforms the conventional methods with respect to the modeling precision and that reconstructions on real photographs have achieved favorable visual effects. Moreover, the comparison results validated the effectiveness of using the 3D face in the proposed pose estimation method.