Details
| Original language | English |
|---|---|
| Title of host publication | 2011 Joint Urban Remote Sensing Event, JURSE 2011 - Proceedings |
| Pages | 293-296 |
| Number of pages | 4 |
| ISBN (electronic) | 9781424486571 |
| Publication status | Published - 5 May 2011 |
| Event | IEEE GRSS and ISPRS Joint Urban Remote Sensing Event, JURSE 2011 - Munich, Germany Duration: 11 Apr 2011 → 13 Apr 2011 |
Publication series
| Name | 2011 Joint Urban Remote Sensing Event, JURSE 2011 - Proceedings |
|---|
Abstract
This paper presents a combined bottom-up and top-down approach to 3D roof plane detection and segmentation from laser scanning point clouds. Laser scanning data of city scenes often shows noise and incompleteness because of, e.g., the clutter by trees and the reflection of windows/waterlogged depressions on the roof. Results of the bottom-up plane reconstruction may thus be limited to a number of incomplete and/or irregular regions. We proposed a joint multiple-plane detection scheme to improve the performance of the 3D Hough transform. A model-driven segmentation, which works with the constraint-rules derived from the basic roof model, is conducted to overcome the clutter and flaws in the point cloud ensuring a plausible reconstruction.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
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2011 Joint Urban Remote Sensing Event, JURSE 2011 - Proceedings. 2011. p. 293-296 5764777 (2011 Joint Urban Remote Sensing Event, JURSE 2011 - Proceedings).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Rule-based roof plane detection and segmentation from laser point clouds
AU - Huang, Hai
AU - Brenner, Claus
PY - 2011/5/5
Y1 - 2011/5/5
N2 - This paper presents a combined bottom-up and top-down approach to 3D roof plane detection and segmentation from laser scanning point clouds. Laser scanning data of city scenes often shows noise and incompleteness because of, e.g., the clutter by trees and the reflection of windows/waterlogged depressions on the roof. Results of the bottom-up plane reconstruction may thus be limited to a number of incomplete and/or irregular regions. We proposed a joint multiple-plane detection scheme to improve the performance of the 3D Hough transform. A model-driven segmentation, which works with the constraint-rules derived from the basic roof model, is conducted to overcome the clutter and flaws in the point cloud ensuring a plausible reconstruction.
AB - This paper presents a combined bottom-up and top-down approach to 3D roof plane detection and segmentation from laser scanning point clouds. Laser scanning data of city scenes often shows noise and incompleteness because of, e.g., the clutter by trees and the reflection of windows/waterlogged depressions on the roof. Results of the bottom-up plane reconstruction may thus be limited to a number of incomplete and/or irregular regions. We proposed a joint multiple-plane detection scheme to improve the performance of the 3D Hough transform. A model-driven segmentation, which works with the constraint-rules derived from the basic roof model, is conducted to overcome the clutter and flaws in the point cloud ensuring a plausible reconstruction.
UR - http://www.scopus.com/inward/record.url?scp=79957631897&partnerID=8YFLogxK
U2 - 10.1109/JURSE.2011.5764777
DO - 10.1109/JURSE.2011.5764777
M3 - Conference contribution
AN - SCOPUS:79957631897
SN - 9781424486571
T3 - 2011 Joint Urban Remote Sensing Event, JURSE 2011 - Proceedings
SP - 293
EP - 296
BT - 2011 Joint Urban Remote Sensing Event, JURSE 2011 - Proceedings
T2 - IEEE GRSS and ISPRS Joint Urban Remote Sensing Event, JURSE 2011
Y2 - 11 April 2011 through 13 April 2011
ER -