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Realistic Modeling of Water Droplets for Monocular Adherent Raindrop Recognition Using Bézier Curves

  • Martin Roser
  • Julian Kurz
  • Andreas Geiger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6469)

Abstract

In this paper, we propose a novel raindrop shape model for the detection of view-disturbing, adherent raindrops on inclined surfaces. Whereas state-of-the-art techniques do not consider inclined surfaces because they assume the droplets as sphere sections with equal contact angles, our model incorporates cubic Bézier curves that provide a low dimensional and physically interpretable representation of a raindrop surface. The parameters are empirically deduced from numerous observations of different raindrop sizes and surface inclination angles. It can be easily integrated into a probabilistic framework for raindrop recognition, using geometrical optics to simulate the visual raindrop appearance. In comparison to a sphere section model, the proposed model yields an improved droplet surface accuracy up to three orders of magnitude.

Keywords

Contact Angle Inclination Angle Water Droplet Geometrical Optic Incline Surface 
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

  • Martin Roser
    • 1
  • Julian Kurz
    • 1
  • Andreas Geiger
    • 1
  1. 1.Department of Measurement and ControlKarlsruhe Institute of Technology (KIT)KarlsruheGermany

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