Real-time scene reconstruction and triangle mesh generation using multiple RGB-D cameras
In: Journal of Real-Time Image Processing Journal of Real-Time Image Processing, Springer Verlag, 2019, ⟨10.1007/s11554-017-0736-x⟩; (2019-12-01)
Online
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Zugriff:
International audience; We present a novel 3D reconstruction system that can generate a stable triangle mesh using data from multiple RGB-D sensors in real time for dynamic scenes. The first part of the system uses moving least squares (MLS) point set surfaces to smooth and filter point clouds acquired from RGB-D sensors. The second part of the system generates triangle meshes from point clouds. The whole pipeline is executed on the GPU and is tailored to scale linearly with the size of the input data. Our contributions include changes to the MLS method for improving meshing, a fast triangle mesh generation method and GPU implementations of all parts of the pipeline.
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Real-time scene reconstruction and triangle mesh generation using multiple RGB-D cameras
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| Autor/in / Beteiligte Person: | Nozick, Vincent ; Meerits, Siim ; Saito, Hideo ; hyper vision research lab (hvrl) ; Laboratoire d'Informatique Gaspard-Monge (LIGM) ; Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique (CNRS) ; Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM) |
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| Quelle: | Journal of Real-Time Image Processing Journal of Real-Time Image Processing, Springer Verlag, 2019, ⟨10.1007/s11554-017-0736-x⟩; (2019-12-01) |
| Veröffentlichung: | HAL CCSD, 2019 |
| Medientyp: | unknown |
| ISSN: | 1861-8200 (print) ; 1861-8219 (print) |
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