• DocumentCode
    440203
  • Title

    Robust object segmentation and parametrization of 3D lidar data

  • Author

    Kapp, Andreas

  • Author_Institution
    Inst. fur Mess- und Regelungstechnik, Karlsruhe Univ., Germany
  • fYear
    2005
  • fDate
    6-8 June 2005
  • Firstpage
    694
  • Lastpage
    699
  • Abstract
    This article addresses the problem of robust signal processing of 3D lidar data prone to noise. After describing the characteristics of the lidar data given we describe how the data can be segmented in a robust manner. The approach is based on edge detection followed by region growing. We show how the segments can be described using parametric models. In the final step the segments are circumscribed using appropriate bounding objects. We motivate the individual steps of our approach and light up the mathematical background.
  • Keywords
    automated highways; edge detection; image segmentation; object detection; optical radar; 3D lidar data; edge detection; object parametrization; object segmentation; region growing; robust signal processing; Goniometers; Image edge detection; Image segmentation; Integrated circuit noise; Laser radar; Noise robustness; Object segmentation; Parameter estimation; Signal processing; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium, 2005. Proceedings. IEEE
  • Print_ISBN
    0-7803-8961-1
  • Type

    conf

  • DOI
    10.1109/IVS.2005.1505184
  • Filename
    1505184