3D OCTREE BASED WATERTIGHT MESH GENERATION FROM UBIQUITOUS DATA

• Published in: International archives of the photogrammetry, remote sensing and spatial information sciences. Vol. XL-3/W3; no. 3; pp. 613 - 617
• Main Authors: Caraffa, L., Brédif, M., Vallet, B.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Gottingen Copernicus GmbH 01.01.2015; Copernicus Publications
• ISSN: 2194-9034; 1682-1750; 2194-9034
• DOI: 10.5194/isprsarchives-XL-3-W3-613-2015

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.