Realistic 3D face modeling using feature-preserving surface registration

摘要

This paper presents a novel algorithm for realistic 3D face modeling from a single pair of color and time-of-flight (TOF) depth images using a generic, deformable model. Most previous approaches have attempted to emphasize either facial feature or global shape consistency, resulting in either visually plausible or geometrically accurate models. In this paper, we introduce feature-preserving surface registration to achieve both reality and accuracy. The proposed algorithm takes advantages of both facial features from the color image and geometric information from the depth image in an iterative closest point (ICP) framework, where the non-rigid registration is achieved by iteratively minimizing the energy function consisting of feature distance term, surface distance term, and linear elasticity term. As demonstrated in the experimental results, the proposed algorithm builds the personalized 3D face model within a few seconds with high visual quality.