ABSTRACT:Thanks to a hybrid georeferencing unit coupling GNSS and IMU sensors, mobile mapping systems (MMS) with lidar sensors provide accurate 3D point clouds of the acquired areas, mainly urban cities. When dealing with several acquisitions of the same area with the same device, differences in the range of several tens of centimeters can be observed. Such degradation of the georeferencing accuracies are due to two main reasons: inertial drift and losses of GNSS signals in urban corridors. The purpose of this paper is therefore to correct these differences with an accurate ICP-based registration algorithm, and then to correct the MMS trajectory using these retrieved local transformation parameters.The trajectory loop information plays a key role for that purpose. We propose a four-step method starting from a 3D point cloud with overlapping parts, and the trajectory of the mobile mapping system. First, a polygonal approximation of the trajectory is computed in order to first divide the whole registration problem in local sub-issues. Secondly, we aim to find all the potential overlapping acquired areas between these segments using simple bounding box intersections. Thirdly, for each pair of overlapping areas, an efficient variant of the ICP algorithm is proposed to (1) prune cases where segments do not share point clouds of the same areas and (2) retrieve the transformation parameters, for real overlapping cases. Finally, all these transformations are linked together, and fed into a global distance compensation problem, allowing to adjust the MMS trajectories for several passages. As a conclusion, this method is successfully applied to data acquired over Paris (France) with the Stereopolis mobile mapping system.

Abstract

Nous présentons dans cet article un système de numérisation mobile 3D hybride laser-image qui permet d'acquérir des infrastructures de données spatiales répondant aux besoins d'applications diverses allant de navigations multimédia immersives jusqu'à de la métrologie 3D à travers le web. Nous détaillons la conception du système, ses capteurs, son architecture et sa calibration, ainsi qu'un service web offrant la possibilité de saisir en 3D via un outil de type SaaS (Software as a Service), permettant à tout un chacun d'enrichir ses propres bases de données à hauteur de ses besoins.Nous abordons également l'anonymisation des données, à savoir la détection et le floutage de plaques d'immatriculation, qui est est une étape inévitable pour la diffusion de ces données sur Internet via des applications grand public.

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ABSTRACT:This paper proposes a pipeline to produce road orthophoto and DTM from Mobile Laser Scanning (MLS). For the ortho, modern laser scanners provide a reflectance information allowing for high quality grayscale images, at a much finer resolution than aerial photography can offer. For DTM, MLS offers a much higher accuracy and density than aerial products. This increased precision and resolution leverages new applications for both ortho and DEM. The first task is to filter ground vs non ground, then an interpolation is conducted to build image tiles from the filtered points. Finally, multiple layers are registered and blended to allow for seamless fusion. Our proposed approach achieves high quality products and scaling up is demonstrated.