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3D Reconstruction Using an n-Layer Heightmap

  • David Gallup
  • Marc Pollefeys
  • Jan-Michael Frahm
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6376)

Abstract

We present a novel method for 3D reconstruction of urban scenes extending a recently introduced heightmap model. Our model has several advantages for 3D modeling of urban scenes: it naturally enforces vertical surfaces, has no holes, leads to an efficient algorithm, and is compact in size. We remove the major limitation of the heightmap by enabling modeling of overhanging structures. Our method is based on an an n-layer heightmap with each layer representing a surface between full and empty space. The configuration of layers can be computed optimally using a dynamic programming method. Our cost function is derived from probabilistic occupancy, and incorporates the Bayesian Information Criterion (BIC) for selecting the number of layers to use at each pixel. 3D surface models are extracted from the heightmap. We show results from a variety of datasets including Internet photo collections. Our method runs on the GPU and the complete system processes video at 13 Hz.

Keywords

Bayesian Information Criterion Occupancy Grid Probabilistic Occupancy Photo Collection Urban Scene 
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 2010

Authors and Affiliations

  • David Gallup
    • 1
  • Marc Pollefeys
    • 2
  • Jan-Michael Frahm
    • 1
  1. 1.Department of Computer ScienceUniversity of North Carolina 
  2. 2.Department of Computer ScienceETH Zurich 

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