Real-time scene reconstruction and triangle mesh generation using multiple RGB-D cameras

Abstract : 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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https://hal-upec-upem.archives-ouvertes.fr/hal-01638241
Contributeur : Vincent Nozick <>
Soumis le : mardi 26 décembre 2017 - 01:53:48
Dernière modification le : mercredi 4 juillet 2018 - 16:33:28
Document(s) archivé(s) le : mardi 27 mars 2018 - 12:16:06

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Siim Meerits, Vincent Nozick, Hideo Saito. Real-time scene reconstruction and triangle mesh generation using multiple RGB-D cameras. Journal of Real-Time Image Processing, Springer Verlag, 2017, 〈10.1007/s11554-017-0736-x〉. 〈hal-01638241〉

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