Abstract
Abstract. The representation of 3D geometric and photometric information of the real world is one of the most challenging and extensively studied research topics in the photogrammetry and robotics communities. In this paper, we present a fully automatic framework for 3D high quality large scale urban texture mapping using oriented images and LiDAR scans acquired by a terrestrial Mobile Mapping System (MMS). First, the acquired points and images are sliced into temporal chunks ensuring a reasonable size and time consistency between geometry (points) and photometry (images). Then, a simple, fast and scalable 3D surface reconstruction relying on the sensor space topology is performed on each chunk after an isotropic sampling of the point cloud obtained from the raw LiDAR scans. Finally, the algorithm proposed in (Waechter et al., 2014) is adapted to texture the reconstructed surface with the images acquired simultaneously, ensuring a high quality texture with no seams and global color adjustment. We evaluate our full pipeline on a dataset of 17 km of acquisition in Rouen, France resulting in nearly 2 billion points and 40000 full HD images. We are able to reconstruct and texture the whole acquisition in less than 30 computing hours, the entire process being highly parallel as each chunk can be processed independently in a separate thread or computer.
Highlights
Mobile Mapping Systems (MMS) have become more and more popular to map cities from the ground level, allowing for a very interesting compromise between level of detail and productivity
Such MMS are increasingly becoming hybrid, acquiring both images and LiDAR point clouds of the environment. These two modalities remain essentially exploited independently, and few works propose to process them jointly. Such a joint exploitation would benefit from the high complementarity of these two sources of information: We believe that this trend will accelerate, such that the geospatial industry will have an increasing need for efficient and high quality surface reconstruction and texturing algorithms that scale up to the massive amounts of data that these new means of acquisition produce
Textured meshes are gaining more and more attention in the geospatial industry as Digital Elevation Models coupled with orthophotos, which were well adapted for high altitude airborne or space-borne acquisition, are not suited for the newer means of acquisition: closer range platforms and oblique imagery
Summary
Mobile Mapping Systems (MMS) have become more and more popular to map cities from the ground level, allowing for a very interesting compromise between level of detail and productivity Such MMS are increasingly becoming hybrid, acquiring both images and LiDAR point clouds of the environment. These two modalities remain essentially exploited independently, and few works propose to process them jointly. Such a joint exploitation would benefit from the high complementarity of these two sources of information: We believe that this trend will accelerate, such that the geospatial industry will have an increasing need for efficient and high quality surface reconstruction and texturing algorithms that scale up to the massive amounts of data that these new means of acquisition produce. We are able to produce a highly accurate surface mesh with a high level of detail and high resolution textures at city scale
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