Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W4, 99-102, 2015
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W4/99/2015/
doi:10.5194/isprsarchives-XL-7-W4-99-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
26 Jun 2015
Segmentation-Based Ground Points Detection from Mobile Laser Scanning Point Cloud
X. Lin and J. Zhang Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100830, China
Keywords: Filtering, Mobile Laser Scanning, Point Cloud, Point Cloud Segmentation Abstract. In most Mobile Laser Scanning (MLS) applications, filtering is a necessary step. In this paper, a segmentation-based filtering method is proposed for MLS point cloud, where a segment rather than an individual point is the basic processing unit. Particularly, the MLS point cloud in some blocks are clustered into segments by a surface growing algorithm, then the object segments are detected and removed. A segment-based filtering method is employed to detect the ground segments. Two MLS point cloud datasets are used to evaluate the proposed method. Experiments indicate that, compared with the classic progressive TIN (Triangulated Irregular Network) densification algorithm, the proposed method is capable of reducing the omission error, the commission error and total error by 3.62%, 7.87% and 5.54% on average, respectively.
Conference paper (PDF, 690 KB)


Citation: Lin, X. and Zhang, J.: Segmentation-Based Ground Points Detection from Mobile Laser Scanning Point Cloud, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W4, 99-102, doi:10.5194/isprsarchives-XL-7-W4-99-2015, 2015.

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