Registration and change detection techniques using 3D laser radar data from natural environments

Gustav Tolt; Anders Wiklund; Pierre Andersson; Tomas Chevalier; Christina Grönwall; Frank Gustafsson; Håkan Larsson

doi:10.1117/12.690189

5 October 2006 Registration and change detection techniques using 3D laser radar data from natural environments

Gustav Tolt, Anders Wiklund, Pierre Andersson, Tomas Chevalier, Christina Grönwall, Frank Gustafsson, Håkan Larsson

Author Affiliations +

Proceedings Volume 6396, Electro-Optical Remote Sensing II; 63960A (2006) https://doi.org/10.1117/12.690189
Event: Optics/Photonics in Security and Defence, 2006, Stockholm, Sweden

Abstract

In this paper, we present techniques related to registration and change detection using 3D laser radar data. First, an experimental evaluation of a number of registration techniques based on the Iterative Closest Point algorithm is presented. As an extension, an approach for removing noisy points prior to the registration process by keypoint detection is also proposed. Since the success of accurate registration is typically dependent on a satisfactorily accurate starting estimate, coarse registration is an important functionality. We address this problem by proposing an approach for coarse 2D registration, which is based on detecting vertical structures (e.g. trees) in the point sets and then finding the transformation that gives the best alignment. Furthermore, a change detection approach based on voxelization of the registered data sets is presented. The 3D space is partitioned into a cell grid and a number of features for each cell are computed. Cells for which features have changed significantly (statistical outliers) then correspond to significant changes.

Citation Download Citation

Gustav Tolt, Anders Wiklund, Pierre Andersson, Tomas Chevalier, Christina Grönwall, Frank Gustafsson, and Håkan Larsson "Registration and change detection techniques using 3D laser radar data from natural environments", Proc. SPIE 6396, Electro-Optical Remote Sensing II, 63960A (5 October 2006); https://doi.org/10.1117/12.690189

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