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Conference Papers 2021 International Conference on 3D Vision (3DV) Year : 2021

Efficiently Distributed Watertight Surface Reconstruction


We present an out-of-core and distributed surface reconstruction algorithm which scales efficiently on arbitrarily large point clouds (with optical centres) and produces a 3D watertight triangle mesh representing the surface of the underlying scene. Surface reconstruction from a point cloud is a difficult problem and existing state of the art approaches are usually based on complex pipelines making use of global algorithms (i.e. Delaunay triangulation, graph-cut optimisation). For one of these approaches, we investigate the distribution of all the steps (in particular Delaunay triangulation and graph-cut optimisation) in order to propose a fully scalable method. We show that the problem can be tiled and distributed across a cloud or a cluster of PCs by paying a careful attention to the interactions between tiles and using Spark computing framework. We confirm the efficiency of this approach with an in-depth quantitative evaluation and the successful reconstruction of a surface from a very large data set which combines more than 350 million aerial and terrestrial LiDAR points.
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hal-03380593 , version 1 (02-12-2021)


  • HAL Id : hal-03380593 , version 1


Laurent Caraffa, Yanis Marchand, Mathieu Brédif, Bruno Vallet. Efficiently Distributed Watertight Surface Reconstruction. 2021 International Conference on 3D Vision (3DV), Dec 2021, London, United Kingdom. ⟨hal-03380593⟩
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