Summarizing Large Scale 3D Point Cloud for Navigation Tasks

Abstract : 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.
Type de document :
Communication dans un congrès
IEEE 20th International Conference on Intelligent Transportation Systems, Oct 2017, Yokohama, Japan
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https://hal.archives-ouvertes.fr/hal-01691568
Contributeur : Cédric Demonceaux <>
Soumis le : mercredi 24 janvier 2018 - 10:21:24
Dernière modification le : lundi 1 octobre 2018 - 09:58:08
Document(s) archivé(s) le : jeudi 24 mai 2018 - 14:17:18

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1570350190.pdf
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  • HAL Id : hal-01691568, version 1

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Imeen Salah, Sebastien Kramm, Cédric Demonceaux, Pascal Vasseur. Summarizing Large Scale 3D Point Cloud for Navigation Tasks. IEEE 20th International Conference on Intelligent Transportation Systems, Oct 2017, Yokohama, Japan. 〈hal-01691568〉

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