Navigability Graph Extraction From Large-Scale 3D Point Cloud

Imeen Salah 1 Sebastien Kramm 1 Cédric Demonceaux 2 Pascal Vasseur 1, 2
2 VIBOT - VIsion pour la roBOTique [VIBOT CNRS ERL 6000]
CNRS - Centre National de la Recherche Scientifique : ERL6000, Le2i - Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508]
Abstract : This paper presents a novel method for summarizing and compression of large-scale 3D models into compact spherical representations. The information is combined into a set of optimized 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 to provide a navigability graph that maximizes the significance of the contents of its nodes while maintaining the full visibility of the environment. Experimental results in summarizing large-scale 3D map demonstrate the feasibility of our approach and evaluate the performance of the algorithm.
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Communication dans un congrès
21st IEEE International Conference on Intelligent Transportation Systems, Nov 2018, Maui, Hawaii, United States
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https://hal.archives-ouvertes.fr/hal-01929921
Contributeur : Cédric Demonceaux <>
Soumis le : mercredi 21 novembre 2018 - 14:47:43
Dernière modification le : vendredi 7 décembre 2018 - 17:14:02

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  • HAL Id : hal-01929921, version 1

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Imeen Salah, Sebastien Kramm, Cédric Demonceaux, Pascal Vasseur. Navigability Graph Extraction From Large-Scale 3D Point Cloud. 21st IEEE International Conference on Intelligent Transportation Systems, Nov 2018, Maui, Hawaii, United States. 〈hal-01929921〉

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