A Space-Time Depth Super-Resolution Scheme for 3D Face Scanning

Abstract

Current 3D imaging solutions are often based on rather specialized and complex sensors, such as structured light camera/projector systems, and require explicit user cooperation for 3D face scanning under more or less controlled lighting conditions. In this paper, we propose a cost effective 3D acquisition solution with a 3D space-time super-resolution scheme which is particularly suited to 3D face scanning. The proposed solution uses a low-cost and easily movable hardware involving a calibrated camera pair coupled with a non calibrated projector device. We develop a hybrid stereovision and phase-shifting approach using two shifted patterns and a texture image, which not only takes advantage of the assets of stereovision and structured light but also overcomes their weaknesses. We carry out a new super-resolution scheme to correct the 3D facial model and to enrich the 3D scanned view. Our scheme performs the super-resolution despite facial expression variation using a CPD non-rigid matching. We demonstrate both visually and quantitatively the efficiency of the proposed technique.