Automatic structure detection in a point-cloud of buildings obtained by terrestrial laser scanning

Qingming Zhan, Qiancong Pang, Wenzhong Shi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In recent years, terrestrial laser scanner (TLS) has become a popular data acquisition tool for producing irregularly-spaced point clouds as well as airborne laser scanning (ALS). Automated detection of structures (roof and ground etc.) based on the point cloud analysis of buildings has become increasingly important. One of the most demanding tasks in TLS is the filtering of the ground and roofs in TLS point clouds. This paper proposes a method for detecting buildings' structures from an irregularly-spaced point-cloud. This method is consisted of segmentation and classification. As the previously developed the segmentation methods can not be applied to it directly, it has to perform twice pre-filtration so as to proceed to further calculation for segmentation and classification. More importantly the algorithm is extensible and future work will further strengthen the algorithm.
Original languageEnglish
Title of host publicationMIPPR 2007
Subtitle of host publicationAutomatic Target Recognition and Image Analysis; and Multispectral Image Acquisition
Volume6786
DOIs
Publication statusPublished - 1 Dec 2007
EventMIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition - Wuhan, China
Duration: 15 Nov 200717 Nov 2007

Conference

ConferenceMIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition
CountryChina
CityWuhan
Period15/11/0717/11/07

Keywords

  • Classification
  • Point clouds
  • Reconstruction
  • Segmentation

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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