INTEGRATION OF BUILDING KNOWLEDGE INTO BINARY SPACE PARTITIONING FOR THE RECONSTRUCTION OF REGULARIZED BUILDING MODELS

Recent approaches for the automatic reconstruction of 3D building models from airborne point cloud data integrate prior knowledge of roof shapes with the intention to improve the regularization of the resulting models without lessening the flexibility to generate all real-world occurring roof shapes...

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Main Authors: A. Wichmann, J. Jung, G. Sohn, M. Kada, M. Ehlers
Format: Article
Language:English
Published: Copernicus Publications 2015-09-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W5/541/2015/isprsannals-II-3-W5-541-2015.pdf
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author A. Wichmann
J. Jung
G. Sohn
M. Kada
M. Ehlers
author_facet A. Wichmann
J. Jung
G. Sohn
M. Kada
M. Ehlers
author_sort A. Wichmann
collection DOAJ
description Recent approaches for the automatic reconstruction of 3D building models from airborne point cloud data integrate prior knowledge of roof shapes with the intention to improve the regularization of the resulting models without lessening the flexibility to generate all real-world occurring roof shapes. In this paper, we present a method to integrate building knowledge into the data-driven approach that uses binary space partitioning (BSP) for modeling the 3D building geometry. A retrospective regularization of polygons that emerge from the BSP tree is not without difficulty because it has to deal with the 2D BSP subdivision itself and the plane definitions of the resulting partition regions to ensure topological correctness. This is aggravated by the use of hyperplanes during the binary subdivision that often splits planar roof regions into several parts that are stored in different subtrees of the BSP tree. We therefore introduce the use of hyperpolylines in the generation of the BSP tree to avoid unnecessary spatial subdivisions, so that the spatial integrity of planar roof regions is better maintained. The hyperpolylines are shown to result from basic building roof knowledge that is extracted based on roof topology graphs. An adjustment of the underlying point segments ensures that the positions of the extracted hyperpolylines result in regularized 2D partitions as well as topologically correct 3D building models. The validity and limitations of the approach are demonstrated on real-world examples.
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spelling doaj.art-e6c942a7964d4ab8bc399b35c0ad26932022-12-21T17:49:44ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502015-09-01II-3-W554154810.5194/isprsannals-II-3-W5-541-2015INTEGRATION OF BUILDING KNOWLEDGE INTO BINARY SPACE PARTITIONING FOR THE RECONSTRUCTION OF REGULARIZED BUILDING MODELSA. Wichmann0J. Jung1G. Sohn2M. Kada3M. Ehlers4Institute for Geoinformatics and Remote Sensing (IGF), University of Osnabrück, Barbarastr. 22b, 49076 Osnabrück, GermanyDepartment of Earth, Space Science and Engineering, York University, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3Department of Earth, Space Science and Engineering, York University, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3Institute for Geoinformatics and Remote Sensing (IGF), University of Osnabrück, Barbarastr. 22b, 49076 Osnabrück, GermanyInstitute for Geoinformatics and Remote Sensing (IGF), University of Osnabrück, Barbarastr. 22b, 49076 Osnabrück, GermanyRecent approaches for the automatic reconstruction of 3D building models from airborne point cloud data integrate prior knowledge of roof shapes with the intention to improve the regularization of the resulting models without lessening the flexibility to generate all real-world occurring roof shapes. In this paper, we present a method to integrate building knowledge into the data-driven approach that uses binary space partitioning (BSP) for modeling the 3D building geometry. A retrospective regularization of polygons that emerge from the BSP tree is not without difficulty because it has to deal with the 2D BSP subdivision itself and the plane definitions of the resulting partition regions to ensure topological correctness. This is aggravated by the use of hyperplanes during the binary subdivision that often splits planar roof regions into several parts that are stored in different subtrees of the BSP tree. We therefore introduce the use of hyperpolylines in the generation of the BSP tree to avoid unnecessary spatial subdivisions, so that the spatial integrity of planar roof regions is better maintained. The hyperpolylines are shown to result from basic building roof knowledge that is extracted based on roof topology graphs. An adjustment of the underlying point segments ensures that the positions of the extracted hyperpolylines result in regularized 2D partitions as well as topologically correct 3D building models. The validity and limitations of the approach are demonstrated on real-world examples.http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W5/541/2015/isprsannals-II-3-W5-541-2015.pdf
spellingShingle A. Wichmann
J. Jung
G. Sohn
M. Kada
M. Ehlers
INTEGRATION OF BUILDING KNOWLEDGE INTO BINARY SPACE PARTITIONING FOR THE RECONSTRUCTION OF REGULARIZED BUILDING MODELS
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title INTEGRATION OF BUILDING KNOWLEDGE INTO BINARY SPACE PARTITIONING FOR THE RECONSTRUCTION OF REGULARIZED BUILDING MODELS
title_full INTEGRATION OF BUILDING KNOWLEDGE INTO BINARY SPACE PARTITIONING FOR THE RECONSTRUCTION OF REGULARIZED BUILDING MODELS
title_fullStr INTEGRATION OF BUILDING KNOWLEDGE INTO BINARY SPACE PARTITIONING FOR THE RECONSTRUCTION OF REGULARIZED BUILDING MODELS
title_full_unstemmed INTEGRATION OF BUILDING KNOWLEDGE INTO BINARY SPACE PARTITIONING FOR THE RECONSTRUCTION OF REGULARIZED BUILDING MODELS
title_short INTEGRATION OF BUILDING KNOWLEDGE INTO BINARY SPACE PARTITIONING FOR THE RECONSTRUCTION OF REGULARIZED BUILDING MODELS
title_sort integration of building knowledge into binary space partitioning for the reconstruction of regularized building models
url http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W5/541/2015/isprsannals-II-3-W5-541-2015.pdf
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