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.
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Karima Ouji, Mohsen Ardabilian, Liming Chen, Faouzi Ghorbel. A Space-Time Depth Super-Resolution Scheme For 3D Face Scanning. ACIVS'2011, IEEE Advanced Concepts for Intelligent Vision Systems Conference, Aug 2011, Het Pand, Ghent, Belgium. pp.658-668, ⟨10.1007/978-3-642-23687-7_59⟩. ⟨hal-01354499⟩

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