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

verfasst von
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.

Organisationseinheit(en)
Geodätisches Institut
Typ
Artikel
Journal
Journal of Applied Geodesy
Band
10
Seiten
27-35
Anzahl der Seiten
9
ISSN
1862-9016
Publikationsdatum
01.03.2016
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Modellierung und Simulation, Ingenieurwesen (sonstige), Erdkunde und Planetologie (sonstige)
Elektronische Version(en)
https://doi.org/10.1515/jag-2015-0020 (Zugang: Geschlossen)
https://doi.org/10.15488/3152 (Zugang: Offen)
 

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