ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-3, 245-250, 2012
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-3/245/2012/
doi:10.5194/isprsannals-I-3-245-2012
© Author(s) 2012. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
20 Jul 2012
TREES DETECTION FROM LASER POINT CLOUDS ACQUIRED IN DENSE URBAN AREAS BY A MOBILE MAPPING SYSTEM
F. Monnier, B. Vallet, and B. Soheilian MATIS research Laboratory, IGN, Avenue de Paris, 94160 Saint Mandé, France
Keywords: terrestrial point cloud, geometrics descriptors, probabilistic relaxation, RANSAC, accumulation map, trees detection Abstract. 3D reconstruction of trees is of great interest in large-scale 3D city modelling. Laser scanners provide geometrically accurate 3D point clouds that are very useful for object recognition in complex urban scenes. Trees often cause important occlusions on building façades. Their recognition can lead to occlusion maps that are useful for many façade oriented applications such as visual based localisation and automatic image tagging. This paper proposes a pipeline to detect trees in point clouds acquired in dense urban areas with only laser informations (x,y, z coordinates and intensity). It is based on local geometric descriptors computed on each laser point using a determined neighbourhood. These descriptors describe the local shape of objects around every 3D laser point. A projection of these values on a 2D horizontal accumulation space followed by a combination of morphological filters provides individual tree clusters. The pipeline is evaluated and the results are presented on a set of one million laser points using a man made ground truth.
Conference paper (PDF, 5253 KB)


Citation: Monnier, F., Vallet, B., and Soheilian, B.: TREES DETECTION FROM LASER POINT CLOUDS ACQUIRED IN DENSE URBAN AREAS BY A MOBILE MAPPING SYSTEM, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-3, 245-250, doi:10.5194/isprsannals-I-3-245-2012, 2012.

BibTeX EndNote Reference Manager XML