3D octree based watertight mesh generation from ubiquitous data

Abstract : Despite of the popularity of Delauney structure for mesh generation, octree based approaches remain an interesting solution for a first step surface reconstruction. In this paper, we propose a generic framework for a octree cell based mesh generation. Its input is a set of Lidar-based 3D measurements or other inputs which are formulated as a set of mass functions that characterize the level of confidence on the occupancy of each octree’s leaf. The output is a binary segmentation of the space between occupied and empty areas by taking into account the uncertainty of data. To this end, the problem is then reduced to a global energy optimization framework efficiently optimized with a min-cut approach. We use the approach for producing a large scale surface reconstruction algorithm by merging data from ubiquitous sources like airborne, terrestrial Lidar data, occupancy map and extra cues. Once the surface is computed, a solution is proposed for texturing the mesh.
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Contributor : Mathieu Brédif <>
Submitted on : Thursday, September 27, 2018 - 11:52:20 AM
Last modification on : Wednesday, October 10, 2018 - 11:30:05 AM

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Laurent Caraffa, Mathieu Brédif, Bruno Vallet. 3D octree based watertight mesh generation from ubiquitous data. ISPRS Geospatial Week 2015, GeoBigData workshop, 2015, La Grande Motte, France. pp.613--617, ⟨10.5194/isprsarchives-XL-3-W3-613-2015⟩. ⟨hal-01882668⟩



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