Automatic Pose Estimation of 3D Facial Models

Pose estimation plays an essential role in many computer vision applications, such as human computer interaction (HCI), driver attentiveness monitoring, face recognition, automatic face model editing, etc. In this paper we propose a geometric feature based pose estimation approach based on 3D facial models. By identifying two clusters of inner eye corners of a 3D facial model, we find the nose tip with the aid of a facial reference plane. Then, a symmetry plane is generated and the pose orientation can be estimated Our proposed algorithm is robust with respect to different persons, large pose variations, different expressions, partial facial data missing, and non-facial outliers. All computation is based on the pure 3D mesh model of a face without texture information. We tested our approach using 1,200 3D raw facial models and 1,200 corresponding clean facial models, and achieved 92.1% and 96.4% correct pose estimation rate, respectively.