AUTOMATIC BUILDING ABSTRACTION FROM AERIAL PHOTOGRAMMETRY
Multi-view stereo has been shown to be a viable tool for the creation of realistic 3D city models. Nevertheless, it still states significant challenges since it results in dense, but noisy and incomplete point clouds when applied to aerial images. 3D city modelling usually requires a different rep...
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Copernicus Publications
2017-09-01
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Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W4/243/2017/isprs-annals-IV-2-W4-243-2017.pdf |
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doaj-4d28ad0ee2614388acd135e9286166a02020-11-24T21:59:07ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502017-09-01IV-2-W424325010.5194/isprs-annals-IV-2-W4-243-2017AUTOMATIC BUILDING ABSTRACTION FROM AERIAL PHOTOGRAMMETRYA. Ley0R. Hänsch1O. Hellwich2Dept. of Computer Vision & Remote Sensing, Technische Universität Berlin, Berlin, GermanyDept. of Computer Vision & Remote Sensing, Technische Universität Berlin, Berlin, GermanyDept. of Computer Vision & Remote Sensing, Technische Universität Berlin, Berlin, GermanyMulti-view stereo has been shown to be a viable tool for the creation of realistic 3D city models. Nevertheless, it still states significant challenges since it results in dense, but noisy and incomplete point clouds when applied to aerial images. 3D city modelling usually requires a different representation of the 3D scene than these point clouds. This paper applies a fully-automatic pipeline to generate a simplified mesh from a given dense point cloud. The mesh provides a certain level of abstraction as it only consists of relatively large planar and textured surfaces. Thus, it is possible to remove noise, outlier, as well as clutter, while maintaining a high level of accuracy.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W4/243/2017/isprs-annals-IV-2-W4-243-2017.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. Ley R. Hänsch O. Hellwich |
spellingShingle |
A. Ley R. Hänsch O. Hellwich AUTOMATIC BUILDING ABSTRACTION FROM AERIAL PHOTOGRAMMETRY ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
A. Ley R. Hänsch O. Hellwich |
author_sort |
A. Ley |
title |
AUTOMATIC BUILDING ABSTRACTION FROM AERIAL PHOTOGRAMMETRY |
title_short |
AUTOMATIC BUILDING ABSTRACTION FROM AERIAL PHOTOGRAMMETRY |
title_full |
AUTOMATIC BUILDING ABSTRACTION FROM AERIAL PHOTOGRAMMETRY |
title_fullStr |
AUTOMATIC BUILDING ABSTRACTION FROM AERIAL PHOTOGRAMMETRY |
title_full_unstemmed |
AUTOMATIC BUILDING ABSTRACTION FROM AERIAL PHOTOGRAMMETRY |
title_sort |
automatic building abstraction from aerial photogrammetry |
publisher |
Copernicus Publications |
series |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
2194-9042 2194-9050 |
publishDate |
2017-09-01 |
description |
Multi-view stereo has been shown to be a viable tool for the creation of realistic 3D city models. Nevertheless, it still states significant
challenges since it results in dense, but noisy and incomplete point clouds when applied to aerial images. 3D city modelling usually
requires a different representation of the 3D scene than these point clouds. This paper applies a fully-automatic pipeline to generate a
simplified mesh from a given dense point cloud. The mesh provides a certain level of abstraction as it only consists of relatively large
planar and textured surfaces. Thus, it is possible to remove noise, outlier, as well as clutter, while maintaining a high level of accuracy. |
url |
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W4/243/2017/isprs-annals-IV-2-W4-243-2017.pdf |
work_keys_str_mv |
AT aley automaticbuildingabstractionfromaerialphotogrammetry AT rhansch automaticbuildingabstractionfromaerialphotogrammetry AT ohellwich automaticbuildingabstractionfromaerialphotogrammetry |
_version_ |
1725848986888175616 |