Scanning face models with desktop cameras

Abstract

Generating face models of humans from video sequences is an important problem in many multimedia applications ranging from teleconferencing to virtual reality. Most practical approaches try to fit a generic face model in the two-dimensional image, and adjust the model parameters to arrive at the final answer. These approaches require the identification of specific landmarks on the face, and this identification routine may or may not be an automated process. In this paper, we present a method for deriving the three-dimensional (3-D) face model from a monocular image sequence, using a few standard results from the affine camera geometry literature in computer vision, and spline-fitting techniques adopted from the nonparametric regression literature in statistics. No prior knowledge of the camera calibration parameters and the shape of the face is required by the system, and the entire process requires no user intervention. The system has been successfully demonstrated to extract the 3-D face structure of humans in several image sequences.