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

Siim Meerits (1) , Vincent Nozick (2) , Hideo Saito (1)

1 hvrl - hyper vision research lab
2 LIGM - Laboratoire d'Informatique Gaspard-Monge

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.

Mots clés: 3D reconstruction; meshing; mesh zippering; RGB-D cameras; GPU

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Traitement des images [eess.IV]; Synthèse d'image et réalité virtuelle [cs.GR]

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, 2019, ⟨10.1007/s11554-017-0736-x⟩. ⟨hal-01638241⟩