Realistic modeling of water droplets for monocular adherent raindrop recognition using Bézier curves

Authors:
Martin Roser;Julian Kurz;Andreas Geiger
Affiliations:
Department of Measurement and Control, Karlsruhe Institute of Technology, Karlsruhe, Germany;Department of Measurement and Control, Karlsruhe Institute of Technology, Karlsruhe, Germany;Department of Measurement and Control, Karlsruhe Institute of Technology, Karlsruhe, Germany
Venue:
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume part II
Year:
2010

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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.