| To monitor the state of their networks, road operators equip them with cameras. Unfortunately, degraded meteorological conditions alter the operation of the transport system, by modifying the behaviour of drivers and by reducing the operation range of the sensors. A vision-based traffic
monitoring approach is proposed to take fog and rain into account and react accordingly. A background modeling approach, classically based on a mixture of gaussians, is used to separate the foreground from the background. Since fog is a steady weather, the background image is used to detect, to quantify it and to restore the images. Since rain is a dynamic phenomenon, the foreground is used to detect it and rain streaks are removed from it accordingly. The different detection algorithms are shortly described and illustrated using actual images to foresee their potential benefits. The proposed algorithms may be implemented in existing video-based traffic monitoring systems and may allow the multiplication of applications running on roadside cameras, so as to reduce their installation cost. |
Publications- Hautière, N., Bossu, J., Bigorgne, E. and Aubert, D. Détection de conditions de visibilité réduite par caméra bord de
voies. In Prévention des Risques et Aides à la Conduite, Paris, France, 2010.
 - Hautière, N., Bossu, J., Bigorgne, E., Hiblot, N., Boubezoul,
A., Lusetti, B. and Aubert, D. Sensing the visibility range at low cost in the SAFESPOT road-side
unit. In ITS World Congress (ITS'09), Stockholm, Sweden, 2009.
- Hautière, N., Bigorgne, E., Bossu, J. and Aubert, D. Meteorological Conditions Processing for Vision-based Traffic Monitoring. In IEEE International Workshop on Visual Surveillance (VS'08), Marseille,
France, 2008.
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