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Ransac Approach for Automated Registration of Terrestrial Laser Scans Using Linear Features : Volume Ii-5/W2, Issue 1 (16/10/2013)

By Al-durgham, K.

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Book Id: WPLBN0004014083
Format Type: PDF Article :
File Size: Pages 6
Reproduction Date: 2015

Title: Ransac Approach for Automated Registration of Terrestrial Laser Scans Using Linear Features : Volume Ii-5/W2, Issue 1 (16/10/2013)  
Author: Al-durgham, K.
Volume: Vol. II-5/W2, Issue 1
Language: English
Subject: Science, Isprs, Annals
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2013
Publisher: Copernicus Gmbh, Göttingen, Germany

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Kwak, E., Habib, A., & Al-Durgham, K. (2013). Ransac Approach for Automated Registration of Terrestrial Laser Scans Using Linear Features : Volume Ii-5/W2, Issue 1 (16/10/2013). Retrieved from http://community.worldlibrary.net/


Description
Description: Department of Geomatics Engineering, University of Calgary, Calgary, Alberta, Canada. The registration process of terrestrial laser scans (TLS) targets the problem of how to combine several laser scans in order to attain better information about features than what could be obtained through single scan. The main goal of the registration process is to estimate the parameters which determine geometrical variation between the origins of datasets collected from different locations. Scale, shifts, and rotation parameters are usually used to describe such variation. This paper presents a framework for the registration of overlapping terrestrial laser scans by establishing an automatic matching strategy that uses 3D linear features. More specifically, invariant separation characteristics between 3D linear features extracted from laser scans will be used to establish hypothesized conjugate linear features between the laser scans. These candidate matches are then used to geo-reference scans relative to a common reference frame. The registration workflow simulates the well-known RANndom Sample Consensus method (RANSAC) for determining the registration parameters, whereas the iterative closest projected point (ICPP) is utilized to determine the most probable solution of the transformation parameters from several solutions. The experimental results prove that the proposed methodology can be used for the automatic registration of terrestrial laser scans using linear features.

Summary
RANSAC approach for automated registration of terrestrial laser scans using linear features

 

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