Rule-based Segmentation of Lidar Point Cloud for Automatic Extraction of Building Roof Planes

@inproceedings{Awrangjeb2013RulebasedSO,
  title={Rule-based Segmentation of Lidar Point Cloud for Automatic Extraction of Building Roof Planes},
  author={Mohammad Awrangjeb and Clive S. Fraser and Mohammad. Awrangjeb},
  year={2013}
}
This paper presents a new segmentation technique for LIDAR point cloud data for automatic extraction of building roof planes. Using the ground height from a DEM (Digital Elevation Model), the raw LIDAR points are separated into two groups: ground and nonground points. The ground points are used to generate a ‘building mask’ in which the black areas represent the ground where there are no laser returns below a certain height. The non-ground points are segmented to extract the planar roof… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-9 of 9 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 26 references

A multi-resolution hybrid approach for building model reconstruction from LIDAR data

  • M. Satari, F. Samadzadegan, A. Azizi, H. G. Maas
  • The Photogrammetric Record
  • 2012
Highly Influential
5 Excerpts

The ISPRS benchmark on urban object classification and 3D building reconstruction

  • F. Rottensteiner, G. Sohn, +4 authors U. Breitkopf
  • 2012
Highly Influential
2 Excerpts

Urban building roof segmentation from airborne LIDAR point clouds

  • D. Chen, L. Zhang, J. Li, R. Liu
  • International Journal of Remote Sensing
  • 2012
1 Excerpt

Similar Papers

Loading similar papers…