Skip to Main content Skip to Navigation
Journal articles

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.
Complete list of metadatas

https://hal-upec-upem.archives-ouvertes.fr/hal-01638241
Contributor : Vincent Nozick <>
Submitted on : Tuesday, December 26, 2017 - 1:53:48 AM
Last modification on : Monday, May 11, 2020 - 6:07:07 PM
Long-term archiving on: : Tuesday, March 27, 2018 - 12:16:06 PM

File

Meerits_et_al-2017-Journal_of_...
Publisher files allowed on an open archive

Identifiers

Citation

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

Share

Metrics

Record views

337

Files downloads

626