Name
Abstract | ||
|---|---|---|
Compared to daytime, a larger proportion of accident happens during nighttime. The altered visibility of the road scene for the drivers may partially explain this situation. The latter becomes worse in fog presence. In this paper, two camera-based methods are proposed to detect the presence of night fog in images grabbed by in-vehicle multipurpose cameras. They rely on the visual effects of night fog. A first approach can assess the presence of fog around the vehicle thanks to the detection of the backscattered veil induced by the vehicle ego lights. It aims at detecting fog when the vehicle is alone in absence of exterior public lighting. A second approach can assess the presence of fog thanks to the detection of halos around light sources in the vehicle environment. It aims at detecting fog in presence of road traffic or public lighting. Both methods are presented and illustrated with actual images of fog. Their complementarity makes it possible to envision a complete night fog detection system. There are numerous applications for such a system: automation or adaptation of vehicle lights, contextual speed computation and reliability improvement for camera-based systems. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IVS.2011.5940486 | Intelligent Vehicles Symposium |
Keywords | Field | DocType |
backscatter,cameras,fog,object detection,road accidents,road safety,road vehicles,street lighting,traffic engineering computing,accident,backscattered veil detection,camera-based method,contextual speed computation,exterior public lighting,fog presence,in-vehicle multipurpose cameras,light source halo detection,night fog detection,night fog visual effects,road scene altered visibility,road traffic,vehicle ego lights,vehicle environment,vehicle light adaptation | Object detection,Computer vision,Visibility,Computer science,Backscatter,Road traffic,Automation,Artificial intelligence | Conference |
ISSN | ISBN | Citations |
1931-0587 | 978-1-4577-0890-9 | 9 |
PageRank | References | Authors |
0.66 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Romain Gallen | 1 | 26 | 3.22 |
| Aurélien Cord | 2 | 166 | 9.84 |
| Nicolas Hautiére | 3 | 572 | 28.07 |
| Didier Aubert | 4 | 361 | 35.97 |