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Outlier detection by the EM algorithm for laser scanning in rectangular and polar coordinate systems

  • Karl-Rudolf Koch EMAIL logo and Boris Kargoll
Published/Copyright: July 13, 2015
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Abstract

To visualize the surface of an object, laser scanners determine the rectangular coordinates of points of a grid on the surface of the object in a local coordinate system. Vertical angles, horizontal angles and distances of a polar coordinate system are measured with the scanning. Outliers generally occur as gross errors in the distances. It is therefore investigated here whether rectangular or polar coordinates are better suited for the detection of outliers. The parameters of a surface represented by a polynomial are estimated in the nonlinear Gauss Helmert (GH) model and in a linear model. Rectangular and polar coordinates are used, and it is shown that the results for both coordinate systems are identical. It turns out that the linear model is sufficient to estimate the parameters of the polynomial surface. Outliers are therefore identified in the linear model by the expectation maximization (EM) algorithm for the variance-inflation model and are confirmed by the EM algorithm for the mean-shift model. Again, rectangular and polar coordinates are used. The same outliers are identified in both coordinate systems.

Acknowledgments

The authors are indebted to Maria Hennes for pointing out the task of using rectangular and polar coordinates in the GH model, to Wolf-Dieter Schuh for valuable comments and to Ernst-Martin Blome for assistance with the measurements.

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Received: 2015-4-4
Accepted: 2015-5-19
Published Online: 2015-7-13
Published in Print: 2015-9-1

© 2015 Walter de Gruyter GmbH, Berlin/Munich/Boston

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