This paper employs a new technology for modeling textured 3D faces. 3D faces can either be generated automatically from one or more photographs, or modeled directly through an intuitive user interface. Users are assisted in two key problems of computer-aided face modeling. It presents two algorithms for 3D face modeling from an image sequence. The first method works by creating an initial estimate using multiframe structure from motion (SfM) reconstruction framework, which is refined by comparing against a generic face model. The comparison is carried out using an energy-function optimization strategy. Results of 3D reconstruction algorithm are presented. The second method presented reconstructs a face model by adapting a generic model to contours of a face over all the frames of an image sequence. The algorithm for pose estimation and 3D face reconstruction relies solely on contours and the system does not require knowledge of rendering parameters (e.g. light direction and intensity). Results relying on finding accurate point correspondences across frames is presented.