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

authored by

Johannes Bureick, Hamza Alkhatib, Ingo Neumann

Abstract

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.

Organisation(s)

Geodetic Institute

Type

Article

Journal

Journal of Applied Geodesy

Volume

10

Pages

27-35

No. of pages

9

ISSN

1862-9016

Publication date

01.03.2016

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Modelling and Simulation, Engineering (miscellaneous), Earth and Planetary Sciences (miscellaneous)

Electronic version(s)

https://doi.org/10.1515/jag-2015-0020 (Access: Closed)
https://doi.org/10.15488/3152 (Access: Open)

 

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