Towards video processing in vehicles under adverse weather conditions
2012
In this contribution we propose methods for vehicle detection and tracking for the Advanced Driver Assistance
Systems (ADAS) that work under extremely adverse weather conditions. Most of the state-of-the-art vehicle
detection and tracking methods are based either on appearance based vehicle recognition or on extraction and
tracking of dedicated image key points. Visibility deterioration due to rain drops and water streaks on the
windshield, swirling spray, and fog lead to a drastic performance reduction or even to a complete failure of these
approaches. In this contribution we propose several methods for coping with these phenomena. In addition to
an extension of the feature-based tracking method, which copes with outliers and temporarily disappearing key
points, we present a detection and tracking method based on search for vehicle rear lights and whole rear views
in the saturation channel. Utilization of symmetry operators and search space restriction allows to detect and
track vehicles even in pouring rain conditions. Furthermore, we present two applications of the above-described
methods. Estimation of the strength of spray produced by preceding vehicles allows to draw conclusions about
the overall visibility conditions and to adjust the intensity of one's own rear lights. Besides, a restoration of
deteriorated image regions becomes possible.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
6
References
0
Citations
NaN
KQI