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Speed Up of Shape from Shading Using Graduated Non-convexity

  • Daniele Gelli
  • Domenico Vitulano
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2886)

Abstract

This paper will focus on a proposal to speed up Shape From Shading (SFS) approaches based on energy minimization. To this end, Graduated Non Convexity (GNC) algorithm has been adopted to minimize this strongly non convex energy. Achieved results are very promising and involve aspects both theoretical and practical. In fact, both a generalization of the original formulation of GNC and an effective discrete shape recovery characterize our approach. Finally, a drastic reduction of the computational time is reached in comparison with the other currently available approaches.

Keywords

IEEE Transaction Machine Intelligence Regularization Term Vision Computing Convex Approximation 
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 2003

Authors and Affiliations

  • Daniele Gelli
    • 1
  • Domenico Vitulano
    • 1
  1. 1.Istituto per le Applicazioni del Calcolo IAC-C.N.R.RomaItaly

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