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Journal of Applied Geodesy

Editor-in-Chief: Kahmen, Heribert / Rizos, Chris

CiteScore 2017: 1.23

SCImago Journal Rank (SJR) 2017: 0.445
Source Normalized Impact per Paper (SNIP) 2017: 1.357

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Volume 10, Issue 1


Robust Spatial Approximation of Laser Scanner Point Clouds by Means of Free-form Curve Approaches in Deformation Analysis

Johannes Bureick / Hamza Alkhatib / Ingo Neumann
Published Online: 2016-03-31 | DOI: https://doi.org/10.1515/jag-2015-0020


In many geodetic engineering applications it is necessary to solve the problem of describing a measured data point cloud, measured, e. g. by laser scanner, by means of free-form curves or surfaces, e. g., with B-Splines as basis functions. The state of the art approaches to determine B-Splines yields results which are seriously manipulated by the occurrence of data gaps and outliers.

Optimal and robust B-Spline fitting depend, however, on optimal selection of the knot vector. Hence we combine in our approach Monte-Carlo methods and the location and curvature of the measured data in order to determine the knot vector of the B-Spline in such a way that no oscillating effects at the edges of data gaps occur. We introduce an optimized approach based on computed weights by means of resampling techniques. In order to minimize the effect of outliers, we apply robust M-estimators for the estimation of control points.

The above mentioned approach will be applied to a multi-sensor system based on kinematic terrestrial laserscanning in the field of rail track inspection.

Keywords: Deformation; Free-form Curve; B-Splines; Knot Adjustment; Robust Parameter Estimation; Monte-Carlo Resampling Techniques


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About the article

Received: 2015-11-19

Accepted: 2015-12-06

Published Online: 2016-03-31

Published in Print: 2016-03-01

Citation Information: Journal of Applied Geodesy, Volume 10, Issue 1, Pages 27–35, ISSN (Online) 1862-9024, ISSN (Print) 1862-9016, DOI: https://doi.org/10.1515/jag-2015-0020.

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