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Summarizing Large Scale 3D Mesh

Abstract : 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 to provide a very compact map that maximizes the significance of its content 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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Contributor : Cédric Demonceaux <>
Submitted on : Friday, August 31, 2018 - 11:14:42 AM
Last modification on : Monday, March 30, 2020 - 8:44:45 AM
Document(s) archivé(s) le : Saturday, December 1, 2018 - 2:09:56 PM


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  • HAL Id : hal-01865249, version 1


Imeen Salah, Sebastien Kramm, Cédric Demonceaux, Pascal Vasseur. Summarizing Large Scale 3D Mesh. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems - IROS, Oct 2018, Madrid, Spain. ⟨hal-01865249⟩



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