A method to detect and remove overlapped points in terrestrial laser scanning data

Soohee Han, Sangmin Kim, Hyokeun Park, Changjae Kim, Joon Heo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In general, terrestrial laser scanners (TLSs) acquire point clouds with sufficient overlaps among scans to improve point density and to produce conjugate features to be used for point cloud registration. In most cases, however, the overlapped data are maintained unfiltered even after the registration is finished and point density exceeded a sufficient level. In the present study, a method is introduced to manage multi-scan data, in which overlapped points are detected and removed. To detect the overlapped points, each point in a lately scanned point cloud is examined if it is too closely located with any one in former scanned point cloud, then overlapped points are removed. The remaining points are merged into the former point cloud, and the process is sequentially applied to all scans. For fast detection of overlapped points, octree is utilized as a 3-dimensional indexing structure.

Original languageEnglish
Title of host publication31st Asian Conference on Remote Sensing 2010, ACRS 2010
Pages465-467
Number of pages3
Publication statusPublished - 2010 Dec 1
Event31st Asian Conference on Remote Sensing 2010, ACRS 2010 - Hanoi, Viet Nam
Duration: 2010 Nov 12010 Nov 5

Publication series

Name31st Asian Conference on Remote Sensing 2010, ACRS 2010
Volume1

Other

Other31st Asian Conference on Remote Sensing 2010, ACRS 2010
CountryViet Nam
CityHanoi
Period10/11/110/11/5

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Han, S., Kim, S., Park, H., Kim, C., & Heo, J. (2010). A method to detect and remove overlapped points in terrestrial laser scanning data. In 31st Asian Conference on Remote Sensing 2010, ACRS 2010 (pp. 465-467). (31st Asian Conference on Remote Sensing 2010, ACRS 2010; Vol. 1).