A Coarse and Relevant 3D Representation for Fast and Lightweight RGB-D Mapping

Bruce Canovas 1 Michèle Rombaut 1 Amaury Nègre 2 Serge Olympieff 1 Denis Pellerin 1
1 GIPSA-AGPIG - AGPIG
GIPSA-DIS - Département Images et Signal
2 GIPSA-Services - GIPSA-Services
GIPSA-lab - Grenoble Images Parole Signal Automatique
Abstract : In this paper we present a novel lightweight and simple 3D representation for real-time dense 3D mapping of static environments with an RGB-D camera. Our approach builds and updates a low resolution 3D model of an observed scene as an unordered set of new primitives called supersurfels, which can be seen as elliptical planar patches, generated from superpixels segmented RGB-D live measurements. While most of the actual solutions focuse on the accuracy of the reconstructed 3D model, the implemented method is well-adapted to run on robots with reduced/limited computing capacity and memory size, which do not need a highly detailed map of their environment but can settle for an approximate one.
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Submitted on : Friday, March 15, 2019 - 11:23:11 AM
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Bruce Canovas, Michèle Rombaut, Amaury Nègre, Serge Olympieff, Denis Pellerin. A Coarse and Relevant 3D Representation for Fast and Lightweight RGB-D Mapping. VISAPP 2019 - International Conference on Computer Vision Theory and Applications, Feb 2019, Prague, Czech Republic. ⟨hal-02068740⟩

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