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Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity

Mostegel, Christian and Prettenthaler, Rudolf and Fraundorfer, Friedrich and Bischof, Horst (2017) Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 904-913. IEEE Xplore. CVPR 2017, 21.-26. Jul 2017, Honolulu.

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Official URL: http://cvpr2017.thecvf.com/program/main_conference

Abstract

In this paper we present a scalable approach for robustly computing a 3D surface mesh from multi-scale multi-view stereo point clouds that can handle extreme jumps of point density (in our experiments three orders of magnitude). The backbone of our approach is a combination of octree data partitioning, local Delaunay tetrahedralization and graph cut optimization. Graph cut optimization is used twice, once to extract surface hypotheses from local Delaunay tetrahedralizations and once to merge overlapping surface hypotheses even when the local tetrahedralizations do not share the same topology. This formulation allows us to obtain a constant memory consumption per sub-problem while at the same time retaining the density independent Interpolation properties of the Delaunay-based optimization. On multiple public datasets, we demonstrate that our Approach is highly competitive with the state-of-the-art in terms of accuracy, completeness and outlier resilience. Further, we demonstrate the multi-scale potential of our approach by processing a newly recorded dataset with 2 billion Points and a point density variation of more than four orders of magnitude - requiring less than 9GB of RAM per process.

Item URL in elib:https://elib.dlr.de/115664/
Document Type:Conference or Workshop Item (Speech)
Title:Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Mostegel, Christianmostegel (at) icg.tugraz.atUNSPECIFIED
Prettenthaler, Rudolfrudolf.prettenthaler (at) tugraz.atUNSPECIFIED
Fraundorfer, Friedrichfriedrich.fraundorfer (at) dlr.deUNSPECIFIED
Bischof, Horstbischof (at) icg.tu-graz.ac.atUNSPECIFIED
Date:2017
Journal or Publication Title:2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 904-913
Publisher:IEEE Xplore
Status:Published
Keywords:3D surface mesh, multi-scale multi-view stereo point clouds, octree data
Event Title:CVPR 2017
Event Location:Honolulu
Event Type:international Conference
Event Dates:21.-26. Jul 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Vabene++ (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Zielske, Mandy
Deposited On:29 Nov 2017 17:39
Last Modified:31 Jul 2019 20:13

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