3D road marking reconstruction from street-level calibrated stereo pairs
This paper presents an automatic approach to road marking reconstruction using stereo pairs acquired by a mobile mapping system in a dense urban area. Two types of road markings were studied: zebra crossings (crosswalks) and dashed lines. These two types of road markings consist of strips having known shape and size. These geometric specifications are used to constrain the recognition of strips. In both cases (i.e. zebra crossings and dashed lines), the reconstruction method consists of three main steps. The first step extracts edge points from the left and right images of a stereo pair and computes 3D linked edges using a matching process. The second step comprises a filtering process that uses the known geometric specifications of road marking objects. The goal is to preserve linked edges that can plausibly belong to road markings and to filter others out. The final step uses the remaining linked edges to fit a theoretical model to the data. The method developed has been used for processing a large number of images. Road markings are successfully and precisely reconstructed in dense urban areas under real traffic conditions.
mobile mapping system photogrammetric computer vision edge matching shape from stereo 3d road marking extraction