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Conference Papers Year : 2015

Planes Detection for Robust Localization and Mapping in RGB-D SLAM Systems

Abstract

This paper describes an extension of the popular simultaneous localisation and mapping system (RGB-D SLAM) introduced by Endres et al. In [2]. RGB-D SLAM uses a moving RGB-D sensor (i.e. A Kinect) to incrementally produce a graph-based camera pose trajectory along with a global 3D map of the environment composed of potentially millions of 3D points. The goal here is to produce a global 3D map which is not only composed of millions of 3D points but also 3D planes as indoor scenes are mostly composed of planar features such as floor, walls, desks and other furnitures. These planes are directly detected within the depth images provided by the sensor and therefore tend to "regularize" the noise and missing data in depth images during the whole RGB-D SLAM process. This process represents a first step towards a more semantic approach of RGB-D SLAM.
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Dates and versions

hal-01261272 , version 1 (25-01-2016)

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Hakim Elchaoui Elghor, David Roussel, Fakhr-Eddine Ababsa, El Houssine Bouyakhf. Planes Detection for Robust Localization and Mapping in RGB-D SLAM Systems. 3rd international conference on 3D Vision (3DV 2015), Oct 2015, Lyon, France. pp.452--459, ⟨10.1109/3DV.2015.73⟩. ⟨hal-01261272⟩
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