A fast method for global depth-map extraction from natural images

  • Authors:
  • Vamsidhar Reddy;Alexander Eichhorn;Jon Yngve Hardeberg;Raju Shrestha

  • Affiliations:
  • Gjøvik University College, Gjøvik, Norway;Simula Research Laboratory, Oslo, Norway;Gjøvik University College, Gjøvik, Norway;Gjøvik University College, Gjøvik, Norway

  • Venue:
  • Proceedings of the 9th European Conference on Visual Media Production
  • Year:
  • 2012

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Abstract

Dense depth-map extraction approaches either suffer from limited accuracy and robustness when run on natural images or from long computation times due to complex global optimizations. Recent improvements in massively parallel execution architectures found in today's graphics processing units motivated us to parallelize the global optimization process. In this article we present our analytical approach and a parallel implementation in OpenCL of a multi-label graph-cut algorithm. Our approach accomodates a third camera perspective through which we can improve occlusion handling in order to generate high quality depth maps. Through experiments on natural images we show that our implementation scales linearly and achieves close-to realtime performance.