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Integrating Disparity Images by Incorporating Disparity Rate

  • Tobi Vaudrey
  • Hernán Badino
  • Stefan Gehrig
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4931)

Abstract

Intelligent vehicle systems need to distinguish which objects are moving and which are static. A static concrete wall lying in the path of a vehicle should be treated differently than a truck moving in front of the vehicle. This paper proposes a new algorithm that addresses this problem, by providing dense dynamic depth information, while coping with real-time constraints. The algorithm models disparity and disparity rate pixel-wise for an entire image. This model is integrated over time and tracked by means of many pixel-wise Kalman filters. This provides better depth estimation results over time, and also provides speed information at each pixel without using optical flow. This simple approach leads to good experimental results for real stereo sequences, by showing an improvement over previous methods.

Keywords

Measurement Count Stereo Camera Pixel Position Depth Direction Occupancy Grid 
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 2008

Authors and Affiliations

  • Tobi Vaudrey
    • 1
  • Hernán Badino
    • 2
  • Stefan Gehrig
    • 3
  1. 1.The University of AucklandAucklandNew Zealand
  2. 2.Johann Wolfgang Goethe UniversityGermany
  3. 3.DaimlerChrysler AG, StuttgartGermany

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