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Dense 3D Reconstruction from Wide Baseline Image Sets

  • Helmut Mayer
  • Jan Bartelsen
  • Heiko Hirschmüller
  • Andreas Kuhn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7474)

Abstract

This paper describes an approach for Structure from Motion (SfM) for wide baselines image sets and its combination with the dense Semiglobal Matching (SGM) 3D reconstruction approach. Our approach for SfM relies on given information concerning image overlap, but can deal with large baselines and produces highly precise camera parameters and 3D points. At the core of our contribution is robust least squares adjustment with full exploitation of the covariance information from affine point matching to bundle adjustment. Reweighting for robust adjustment is based on covariance information for each individual residual. We use points detected based on Differences of Gaussians including scale and orientation information as well as a variant of the five point algorithm. A strategy similar to the Expectation Maximization (EM) algorithm is employed to extend partial solutions. The key characteristics of the approach is reliability obtained by aiming at a high precision in every step. The capabilities of our approach are demonstrated by presenting results for sets consisting of images from the ground and from small Unmanned Aircraft Systems (UASs).

Keywords

Scale Invariant Feature Transform Intrinsic Parameter Camera Parameter Bundle Adjustment Epipolar Line 
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 2012

Authors and Affiliations

  • Helmut Mayer
    • 1
  • Jan Bartelsen
    • 1
  • Heiko Hirschmüller
    • 2
  • Andreas Kuhn
    • 1
    • 2
  1. 1.Institute of Applied Computer ScienceBundeswehr University MunichGermany
  2. 2.Institute for Robotics and MechatronicsGerman Aerospace Center (DLR)Germany

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