Abstract
In this paper, we propose a system to reconstruct 3D face models from monocular image sequences. Our approach is based on adapting a generic 3D face model to a set of sparse 3D data points of face features recovered from a video sequence. In our system, the structure from motion is accomplished by using a robust least square minimization approach that is based on dynamically minimizing a weighted least square energy function. A small number of face feature points are selected and tracked along the video sequence. The face poses at all the frames in the sequence are approximated from a pose estimation process with the generic 3D face model. A structure from motion algorithm based on a robust least square minimization is applied to the entire video sequence to recover the face structure. The adaptation of the generic 3D head model to the recovered 3D face structure is achieved by using a radial basis function interpolation. Experimental results of 3D face model recovery using the proposed algorithm are shown.