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A Dynamic Programming Approach to Reconstructing Building Interiors

  • Alex Flint
  • Christopher Mei
  • David Murray
  • Ian Reid
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6315)

Abstract

A number of recent papers have investigated reconstruction under Manhattan world assumption, in which surfaces in the world are assumed to be aligned with one of three dominant directions [1,2,3,4]. In this paper we present a dynamic programming solution to the reconstruction problem for “indoor” Manhattan worlds (a sub–class of Manhattan worlds). Our algorithm deterministically finds the global optimum and exhibits computational complexity linear in both model complexity and image size. This is an important improvement over previous methods that were either approximate [3] or exponential in model complexity [4]. We present results for a new dataset containing several hundred manually annotated images, which are released in conjunction with this paper.

Keywords

Surface Orientation Wall Segment Dynamic Program Approach Orientation Estimate Dominant Direction 
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

  • Alex Flint
    • 1
  • Christopher Mei
    • 1
  • David Murray
    • 1
  • Ian Reid
    • 1
  1. 1.Dept. Engineering ScienceUniversity of OxfordOxfordUK

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