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

  • Karima Ouji
  • Mohsen Ardabilian
  • Liming Chen
  • Faouzi Ghorbel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6915)

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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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Karima Ouji
    • 1
  • Mohsen Ardabilian
    • 1
  • Liming Chen
    • 1
  • Faouzi Ghorbel
    • 2
  1. 1.LIRIS, Lyon Research Center for Images and Intelligent Information SystemsEcole Centrale de LyonEcullyFrance
  2. 2.GRIFT, Groupe de Recherche en Images et Formes de TunisieEcole Nationale des Sciences de l’InformatiqueTunisie

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