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Generalized Voxel Coloring

  • W. Bruce Culbertson
  • Thomas Malzbender
  • Greg Slabaugh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1883)

Abstract

Image-based reconstruction from randomly scattered views is a challenging problem. We present a new algorithm that extends Seitz and Dyer’s Voxel Coloring algorithm. Unlike their algorithm, ours can use images from arbitrary camera locations. The key problem in this class of algorithms is that of identifying the images from which a voxel is visible. Unlike Kutulakos and Seitz’s Space Carving technique, our algorithm solves this problem exactly and the resulting reconstructions yield better results in our application, which is synthesizing new views. One variation of our algorithm minimizes color consistency comparisons; another uses less memory and can be accelerated with graphics hardware. We present efficiency measurements and, for comparison, we present images synthesized using our algorithm and Space Carving.

Keywords

Input Image Consistency Function Full Visibility Camera Location Reprojection Error 
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 2000

Authors and Affiliations

  • W. Bruce Culbertson
    • 1
  • Thomas Malzbender
    • 1
  • Greg Slabaugh
    • 2
  1. 1.Hewlett-Packard LaboratoriesPalo AltoUSA
  2. 2.Georgia Institute of TechnologyUSA

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