Pattern Analysis for an Automatic and Low-Cost 3D Face Acquisition Technique

This paper proposes an automatic 3D face modeling and localizing technique, based on active stereovision. In the offline stage, the optical and geometrical parameters of the stereosensor are estimated. In the online acquisition stage, alternate complementary patterns are successively projected. The captured right and left images are separately analyzed in order to localize left and right primitives with sub-pixel precision. This analysis also provides us with an efficient segmentation of the informative facial region. Epipolar geometry transforms a stereo matching problem into a one-dimensional search problem. Indeed, we employ an adapted, optimized dynamic programming algorithm to pairs of primitives which are already located in each epiline. 3D geometry is retrieved by computing the intersection of optical rays coming from the pair of matched features. A pipeline of geometric modeling techniques is applied to densify the obtained 3D point cloud, and to mesh and texturize the 3D final face model. An appropriate evaluation strategy is proposed and experimental results are provided.