Volume XL-3/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 613-617, 2015
https://doi.org/10.5194/isprsarchives-XL-3-W3-613-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 613-617, 2015
https://doi.org/10.5194/isprsarchives-XL-3-W3-613-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  20 Aug 2015

20 Aug 2015

3D OCTREE BASED WATERTIGHT MESH GENERATION FROM UBIQUITOUS DATA

L. Caraffa, M. Brédif, and B. Vallet L. Caraffa et al.
  • Universit´e Paris-Est, IGN/SR, MATIS, 73 avenue de Paris, 94160 Saint Mandé, France

Keywords: Surface reconstruction, Octree, Graph-cut, Lidar

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.