Pairwise 3D point cloud registration derived from Terrestrial Laser Scanner (TLS) in static mode is an essential task to produce locally consistent 3D point clouds. In this work, the contributions are twofold. First, a non-iterative scheme by merging the SIFT (Scale Invariant Feature Transform) 3D algorithm and the PFH (Point Feature Histograms) algorithm to find initial approximation of the transformation parameters is proposed. Then, a correspondence model based on a new variant of the ICP (Iterative Closest Point) algorithm to refine the transformation parameters is also proposed. To evaluate the local consistency of the pairwise 3D point cloud registration is used a point-to-distance approach. Experiments were performed using seven pairs of 3D point clouds into an urban area. The results obtained showed that the method achieves point-to-plane RMSE (Root of the Mean Square Error) mean values in the order of 2 centimeters.
A New Variant of the ICP Algorithm for Pairwise 3D Point Cloud Registration
2022-01-01
American Academic Scientific Research Journal for Engineering, Technology, and Sciences; Vol 85 No 1 (2022); 71-88 ; 2313-4402 ; 2313-4410
Article (Journal)
Electronic Resource
English
DDC: | 629 |
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