Abstract

We present a new method for determining the pose of a human head from its 2D image. It does not use any artificial markers put on a face. The basic idea is to use a genericmodel of a human head, which accounts for variation in shape and facial expression. Particularly, a set of 3D curves are used to model the contours of eyes, lips, and eyebrows. A technique called Iterative Closest Curve matching (ICC) is proposed, which aims at recovering the pose by iteratively minimizing the distances between the projected model curves and their closest image curves. Because curves contain richer information (such as curvature and length) than points, ICC is both more robust and more efficient than the well-known iterative closest point matching techniques (ICP). Furthermore, the image can be taken by a camera with unknown internal parameters, which can be recovered by our technique thanks to the 3D model. Preliminary experiments show that the proposed technique is promising and that an accurate pose estimate can be obtained from just one image with a generic head model.