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Road safety is influenced by the accurate placement and visibility of road signs, which are maintained based on inventories of traffic signs. These inventories are created (semi-)automatically from street-level images, based on object detection and classification. These systems often neglect the present complimentary signs (subsigns), although clearly important for the meaning and validity of signs...
Road safety is influenced by the adequate placement of traffic signs. As the visibility of road signs degrades over time due to e.g. aging, vandalism or vegetation coverage, sign maintenance is required to preserve a high road safety. This is commonly performed based on inventories of traffic signs, which should be conducted periodically, as road situations may change and the visibility of signs degrades...
Accurate maps of road markings are useful for many applications, such as road maintenance, improving navigation, and prediction of upcoming road situations within autonomously driving vehicles. This paper introduces a generic and learning-based system for the recognition of road markings from street-level panoramic images. This system starts with an Inverse Perspective Mapping, followed by segmentation...
Combined road marking and traffic sign databases are beneficial for both road maintenance and for usage within navigation devices and autonomous driving vehicles. The combination of both markings and signs completely provides all instructions and legislation for drivers. This paper presents a conceptual system for the automated creation of such combined databases and investigates the benefit of this...
Accurate and up-to-date inventories of lighting poles are of interest to energy companies, beneficial for the transition to energy-efficient lighting and may contribute to a more adequate lighting of streets. This potentially improves social security and reduces crime and vandalism during nighttime. This paper describes a system for automated surveying of lighting poles from street-level panoramic...
Inventories of traffic signs are acquired from street-level images in a semi-automated fashion, employing object detection and classification techniques. This is a challenging task, as signs are captured from different viewpoints and under various weather conditions. Furthermore, many similar signs exist, only differing in minor details, and moreover, sign-like objects occur frequently. Consequently,...
Traffic sign inventories are created for road safety and maintenance based on street-level panoramic images. Due to the large capturing interval, large viewpoint deviations between the different capturings occur. These viewpoint variations complicate the classification procedure, which aims at the selection of the correct sign type, out of a high number of nearly similar sign types, typically resulting...
Accurate inventories of traffic signs are required for road maintenance and increase of the road safety. These inventories can be performed efficiently based on street-level panoramic images. However, this is a challenging problem, as these images are captured under a wide range of weather conditions. Besides this, occlusions and sign deformations occur and many sign look-a-like objects exist. Our...
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