3D Face pose estimation and tracking from a monocular camera

In this paper, we describe a new approach for estimating and tracking three-dimensional (3D) pose of a human face from the face images obtained from a single monocular view with full perspective projection. We assume that the shape of a 3D face can be approximated by an ellipse and that the aspect ratio of 3D face ellipse is given. Given a monocular image of a face, we ®rst perform an ellipse detection to locate the face in the image and the 3D position and orientation of the face are then estimated from the detected image face. The face detection is greatly facilitated by exploring the physiological properties of eyes under a special IR illumination and some geometric constraints. The detected initial face ellipse is then tracked in subsequent frames, allowing to track 3D face pose from frame to frame. Compared with the existing feature-based approaches for face pose estimation, our approach is more robust, since ellipse can be more reliably and robustly detected and tracked. Experimental study using a large number of synthetic and real images demonstrates the accuracy and robustness of the proposed approach.