0000000000248778
AUTHOR
Sebastien Kramm
Summarizing Large Scale 3D Point Cloud for Navigation Tasks
International audience; Democratization of 3D sensor devices makes 3D maps building easier especially in long term mapping and autonomous navigation. In this paper we present a new method for summarizing a 3D map (dense cloud of 3D points). This method aims to extract a summary map facilitating the use of this map by navigation systems with limited resources (smartphones, cars, robots...). This Vision-based summarizing process is applied in a fully automatic way using the photometric, geometric and semantic information of the studied environment.
Summarizing Large Scale 3D Mesh
International audience; Recent progress in 3D sensor devices and in semantic mapping allows to build very rich HD 3D maps very useful for autonomous navigation and localization. However , these maps are particularly huge and require important memory capabilities as well computational resources. In this paper, we propose a new method for summarizing a 3D map (Mesh) as a set of compact spheres in order to facilitate its use by systems with limited resources (smartphones, robots, UAVs, ...). This vision-based summarizing process is applied in a fully automatic way using jointly photometric, geometric and semantic information of the studied environment. The main contribution of this research is…