Surface simplification using quadric error metrics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
The Ball-Pivoting Algorithm for Surface Reconstruction
IEEE Transactions on Visualization and Computer Graphics
Nonlocal Image and Movie Denoising
International Journal of Computer Vision
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Sight distance along the pathway plays a significant role in road safety and in particular, has a clear impact on the choice of speed limits. Mapping visibility distance is thus of importance for road engineers and authorities. While visibility distance criteria are routinely taken into account in road design, few systems exist for evaluating them on existing road networks. Most available systems comprise a target vehicle followed at a constant distance by an observer vehicle. This only allows to check if a given, fixed visibility distance is available: estimating the maximum visibility distance requires several passages, with increasing inter-vehicle intervals. We propose two alternative approaches for estimating the maximum available visibility distance, that exploit 3D models of the road and its close environment. These methods involve only one acquisition vehicle and use either active vision, more specifically 3D range sensing (LIDAR), or passive vision, namely, stereovision. The first approach is based on a Terrestrial LIDAR Mobile Mapping System. The triangulated 3D model of the road and its surroundings provided by the system is used to simulate targets at different distances, which allows for estimation of the maximum geometric visibility distance along the pathway in a quite flexible way. The second approach involves the processing of two views taken by digital cameras on-board an inspection vehicle. After road segmentation, the 3D road model is reconstructed which allows maximum roadway visibility distance estimation. Both approaches are described, evaluated and compared. Their pros and cons with respect to vehicle-following systems are also discussed.