Surface Reconstruction via L1-Minimization

  • Veselin Dobrev
  • Jean-Luc Guermond
  • Bojan Popov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5434)


A surface reconstruction technique based on the L 1- minimization of the variation of the gradient is introduced. This leads to a non-smooth convex programming problem. Well-posedness and convergence of the method is established and an interior point based algorithm is introduced. The L 1-surface reconstruction algorithm is illustrated on various test cases including natural and urban terrain data.


Quadrature Rule Quadrature Point Preconditioned Conjugate Gradient Ematical Programming Gaussian Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Veselin Dobrev
    • 1
  • Jean-Luc Guermond
    • 1
  • Bojan Popov
    • 1
  1. 1.Department of MathematicsTexas A&M UniversityCollege StationUSA

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