Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 245-250 |
| Seitenumfang | 6 |
| Fachzeitschrift | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Jahrgang | 38 |
| Publikationsstatus | Veröffentlicht - 2010 |
| Veranstaltung | ISPRS Technical Commission III Symposium on Photogrammetric Computer Vision and Image Analysis, PCV 2010 - Saint-Mande, Frankreich Dauer: 1 Sept. 2010 → 3 Sept. 2010 |
Abstract
A new method for roof plane detection using multiple aerial images and a point cloud is presented. It takes advantage of the fact that segmentation results for different views look different even if the same parameters are used for the original segmentation algorithm. The point cloud can be generated by image matching or by airborne laserscanning. Plane detection starts by a segmentation that is applied to each of the images. The point cloud is used to determine which image segments correspond to planes. The best plane according to a criterion is selected and matched with segments in the other images. Matching of segments requires a DSM generated from the point cloud, and it takes into account the occlusions in each image. This procedure is repeated until no more planes can be found. After that, planar segments are extracted based on region growing in the point cloud in areas of severe under-segmentation, and the multiple-image segmentation procedure is repeated. Finally, neighbouring regions found to be co-planar are merged. First results are presented for test site with up to nine-fold overlap. Our tests show that the method can deliver a good separation of roof planes under difficult circumstances, though the level of detail that can be achieved is limited by the resolution of the point cloud.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Information systems
- Sozialwissenschaften (insg.)
- Geografie, Planung und Entwicklung
Zitieren
- Standard
- Harvard
- Apa
- Vancouver
- BibTex
- RIS
in: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Jahrgang 38, 2010, S. 245-250.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - Roof plane segmentation by combining multiple images and point clouds
AU - Rottensteiner, Franz
PY - 2010
Y1 - 2010
N2 - A new method for roof plane detection using multiple aerial images and a point cloud is presented. It takes advantage of the fact that segmentation results for different views look different even if the same parameters are used for the original segmentation algorithm. The point cloud can be generated by image matching or by airborne laserscanning. Plane detection starts by a segmentation that is applied to each of the images. The point cloud is used to determine which image segments correspond to planes. The best plane according to a criterion is selected and matched with segments in the other images. Matching of segments requires a DSM generated from the point cloud, and it takes into account the occlusions in each image. This procedure is repeated until no more planes can be found. After that, planar segments are extracted based on region growing in the point cloud in areas of severe under-segmentation, and the multiple-image segmentation procedure is repeated. Finally, neighbouring regions found to be co-planar are merged. First results are presented for test site with up to nine-fold overlap. Our tests show that the method can deliver a good separation of roof planes under difficult circumstances, though the level of detail that can be achieved is limited by the resolution of the point cloud.
AB - A new method for roof plane detection using multiple aerial images and a point cloud is presented. It takes advantage of the fact that segmentation results for different views look different even if the same parameters are used for the original segmentation algorithm. The point cloud can be generated by image matching or by airborne laserscanning. Plane detection starts by a segmentation that is applied to each of the images. The point cloud is used to determine which image segments correspond to planes. The best plane according to a criterion is selected and matched with segments in the other images. Matching of segments requires a DSM generated from the point cloud, and it takes into account the occlusions in each image. This procedure is repeated until no more planes can be found. After that, planar segments are extracted based on region growing in the point cloud in areas of severe under-segmentation, and the multiple-image segmentation procedure is repeated. Finally, neighbouring regions found to be co-planar are merged. First results are presented for test site with up to nine-fold overlap. Our tests show that the method can deliver a good separation of roof planes under difficult circumstances, though the level of detail that can be achieved is limited by the resolution of the point cloud.
KW - Buildings
KW - City Models
KW - Data Fusion
KW - Modelling
KW - Segmentation
UR - http://www.scopus.com/inward/record.url?scp=84923858682&partnerID=8YFLogxK
U2 - 10.15488/1140
DO - 10.15488/1140
M3 - Conference article
AN - SCOPUS:84923858682
VL - 38
SP - 245
EP - 250
JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SN - 1682-1750
T2 - ISPRS Technical Commission III Symposium on Photogrammetric Computer Vision and Image Analysis, PCV 2010
Y2 - 1 September 2010 through 3 September 2010
ER -