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A GPU Implementation of Level Set Multiview Stereo

  • Patrick Labatut
  • Renaud Keriven
  • Jean-Philippe Pons
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3994)

Abstract

Variational methods that evolve surfaces according to PDEs have been quite successful for solving the multiview stereo shape reconstruction problem since [1]. However just like every other algorithm that tackles this problem, their running time is quite high (from dozens of minutes to several hours). Fortunately graphics hardware has shown a great potential for speeding up many low-level computer vision tasks. In this paper, we present the analysis of the different bottlenecks of the original implementation of [2] and show how to efficently port it to GPUs using well-known GPGPU techniques. We finally present some results and discuss the improvements.

Keywords

Input Stream Graphic Card Graphic Hardware Shape Reconstruction Computer Vision Algorithm 
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 2006

Authors and Affiliations

  • Patrick Labatut
    • 1
  • Renaud Keriven
    • 2
  • Jean-Philippe Pons
    • 2
  1. 1.Département d’InformatiqueÉcole normale supérieureParis Cedex 05France
  2. 2.CERTISÉcole Nationale des Ponts et ChausséesMarne-la-Vallée Cedex 2France

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