• DocumentCode
    2716092
  • Title

    On template-based reconstruction from a single view: Analytical solutions and proofs of well-posedness for developable, isometric and conformal surfaces

  • Author

    Bartoli, A. ; Gérard, Y. ; Chadebecq, F. ; Collins, T.

  • Author_Institution
    ISIT, Univ. d´´Auvergne, Clermont-Ferrand, France
  • fYear
    2012
  • fDate
    16-21 June 2012
  • Firstpage
    2026
  • Lastpage
    2033
  • Abstract
    Recovering a deformable surface´s 3D shape from a single view registered to a 3D template requires one to provide additional constraints. A recent approach has been to constrain the surface to deform quasi-isometrically. This is applicable to surfaces of materials such as paper and cloth. Current `closed-form´ solutions solve a convex approximation of the original problem whereby the surface´s depth is maximized under the isometry constraints (this is known as the maximum depth heuristic). No such convex approximation has yet been proposed for the conformal case. We give a unified problem formulation as a system of PDEs for developable, isometric and conformal surfaces that we solve analytically. This has important consequences. First, it gives the first analytical algorithms to solve this type of reconstruction problems. Second, it gives the first algorithms to solve for the exact constraints. Third, it allows us to study the well-posedness of this type of reconstruction: we establish that isometric surfaces can be reconstructed unambiguously and that conformal surfaces can be reconstructed up to a few discrete ambiguities and a global scale. In the latter case, the candidate solution surfaces are obtained analytically. Experimental results on simulated and real data show that our methods generally perform as well as or outperform state of the art approaches in terms of reconstruction accuracy.
  • Keywords
    computational geometry; convex programming; image reconstruction; solid modelling; surface reconstruction; 3D template; PDE; closed-form solutions; conformal surface; convex approximation; deformable surface 3D shape; developable surface; isometric surfaces; isometry constraints; maximum depth heuristic; reconstruction accuracy; single view; surface depth; template-based reconstruction; unified problem formulation; well-posedness; Approximation methods; Equations; Image reconstruction; Numerical models; Shape; Surface reconstruction; Three dimensional displays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4673-1226-4
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2012.6247906
  • Filename
    6247906