A space-time depth super-resolution scheme for 3D face scanning

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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. © 2011 Springer-Verlag.

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APA

Ouji, K., Ardabilian, M., Chen, L., & Ghorbel, F. (2011). A space-time depth super-resolution scheme for 3D face scanning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6915 LNCS, pp. 658–668). https://doi.org/10.1007/978-3-642-23687-7_59

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