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Stereo and Active-Sensor Data Fusion for Improved Stereo Block Matching

  • Stefan-Daniel SuveiEmail author
  • Leon Bodenhagen
  • Lilita Kiforenko
  • Peter Christiansen
  • Rasmus N. Jørgensen
  • Anders G. Buch
  • Norbert Krüger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9730)

Abstract

This paper proposes an algorithm which uses the depth information acquired from an active sensor as guidance for a block matching stereo algorithm. In the proposed implementation, the disparity search interval used for the block matching is reduced around the depth values obtained from the active sensor, which leads to an improved matching quality and denser disparity maps and point clouds. The performance of the proposed method is evaluated by carrying out a series of experiments on 3 different data sets obtained from different robotic systems. We demonstrate with experimental results that the disparity estimation is improved and denser disparity maps are generated.

Keywords

Point Cloud Active Sensor Stereo Match Stereo Camera Block Match 
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.

Notes

Acknowledgement

This work was supported by the projects Patient@home and SAFE Perception which are funded by the Danish Innovation Fond.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Stefan-Daniel Suvei
    • 1
    Email author
  • Leon Bodenhagen
    • 1
  • Lilita Kiforenko
    • 1
  • Peter Christiansen
    • 2
  • Rasmus N. Jørgensen
    • 2
  • Anders G. Buch
    • 1
  • Norbert Krüger
    • 1
  1. 1.University of Southern DenmarkOdense MDenmark
  2. 2.Aarhus UniversityAarhus NDenmark

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