Ego-Motion Estimation Using Rectified Stereo and Bilateral Transfer Function

  • Giorgio Panin
  • Nassir W. Oumer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7431)


We describe an ego-motion algorithm based on dense spatio-temporal correspondences, using semi-global stereo matching (SGM) and bilateral image warping in time. The main contribution is an improvement in accuracy and robustness of such techniques, by taking care of speed and numerical stability, while employing twice the structure and data for the motion estimation task, in a symmetric way. In our approach we keep the tasks of structure and motion estimation separated, respectively solved by the SGM and by our pose estimation algorithm. Concerning the latter, we show the benefits introduced by our rectified, bilateral formulation, that provides at the same time more robustness to noise and disparity errors, at the price of a moderate increase in computational complexity, further reduced by an improved Gauss-Newton descent.


Point Cloud Motion Estimation Stereo Match Visual Servoing Visual Odometry 
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

  • Giorgio Panin
    • 1
  • Nassir W. Oumer
    • 1
  1. 1.Institute for Robotics and MechatronicsGerman Aerospace Center (DLR)WeßlingGermany

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