Obstacle Detection with Stereo Vision for Off-Road Vehicle Navigation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Automatic fog detection and estimation of visibility distance through use of an onboard camera
Machine Vision and Applications
ACM SIGGRAPH 2008 papers
GeoS: Geodesic Image Segmentation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Mitigation of visibility loss for advanced camera-based driver assistance
IEEE Transactions on Intelligent Transportation Systems
Contrast restoration of weather degraded images
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Free-space detection is a primary task for car navigation. Unfortunately, classical approaches have difficulties in adverse weather conditions, in particular in daytime fog. In this paper, a solution is proposed thanks to a contrast restoration approach on images grabbed by an in-vehicle camera. The proposed method improves the state-of-the-art in several ways. First, the segmentation of the fog region of interest is better segmented thanks to the computation of the shortest routes maps. Second, the fog density as well as the position of the horizon line is jointly computed. Then, the method restores the contrast of the road by only assuming that the road is flat and, at the same time, detects the vertical objects. Finally, a segmentation of the connected component in front of the vehicle gives the free-space area. An experimental validation was carried out to foresee the effectiveness of the method. Different results are shown on sample images extracted from video sequences acquired from an in-vehicle camera. The proposed method is complementary to existing free-space area detection methods relying on color segmentation and stereovision.