Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 331-335, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
09 Jun 2016
c Mezian, Bruno Vallet, Bahman Soheilian, and Nicolas Paparoditis Universite Paris-Est, IGN, SRIG, MATIS, 73 avenue de Paris, 94160 Saint Mande, France
Keywords: Mobile mapping, Laser scanner, Uncertainty propagation, Error ellipsoid Abstract. Laser scanners are used more and more in mobile mapping systems. They provide 3D point clouds that are used for object reconstruction and registration of the system. For both of those applications, uncertainty analysis of 3D points is of great interest but rarely investigated in the literature. In this paper we present a complete pipeline that takes into account all the sources of uncertainties and allows to compute a covariance matrix per 3D point. The sources of uncertainties are laser scanner, calibration of the scanner in relation to the vehicle and direct georeferencing system. We suppose that all the uncertainties follow the Gaussian law. The variances of the laser scanner measurements (two angles and one distance) are usually evaluated by the constructors. This is also the case for integrated direct georeferencing devices. Residuals of the calibration process were used to estimate the covariance matrix of the 6D transformation between scanner laser and the vehicle system. Knowing the variances of all sources of uncertainties, we applied uncertainty propagation technique to compute the variance-covariance matrix of every obtained 3D point. Such an uncertainty analysis enables to estimate the impact of different laser scanners and georeferencing devices on the quality of obtained 3D points. The obtained uncertainty values were illustrated using error ellipsoids on different datasets.
Conference paper (PDF, 2704 KB)

Citation: Mezian, C., Vallet, B., Soheilian, B., and Paparoditis, N.: UNCERTAINTY PROPAGATION FOR TERRESTRIAL MOBILE LASER SCANNER, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 331-335,, 2016.

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