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A Comparative Study of Two Vertical Road Modelling Techniques

  • Konstantin Schauwecker
  • Reinhard Klette
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6469)

Abstract

Binocular vision combined with stereo matching algorithms can be used in vehicles to gather data of the spatial proximity. To utilize this data we propose a new method for modeling the vertical road profile from a disparity map. This method is based on a region-growing technique, which iteratively performs a least-squares fit of a B-spline curve to a region of selected points. We compare this technique to two variants of the v-disparity method using either an envelope function or a planarity assumption. Our findings are that the proposed road-modeling technique outperforms both variants of the v-disparity technique, for which the planarity assumption is slightly better than the envelope version.

Keywords

Road Surface Automatic Vehicle Guidance Stereo Pair Driver Assistant System Obstacle Detection 
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 2011

Authors and Affiliations

  • Konstantin Schauwecker
    • 1
  • Reinhard Klette
    • 1
  1. 1.Computer Science DepartmentThe University of AucklandAucklandNew Zealand

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