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Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features

A. Kirsch, A. Günter, M. König, Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features, Hochschule Bielefeld, 2022.

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Abstract
Point cloud registration is often used in fields like SLAM where the overlap of two consecutive point clouds is large. But in fields like multi-sensor fusion of point clouds and LiDAR-based localization, there is a high chance of registering non-overlapping point cloud pairs. Since in such cases, the result will always be a wrong transformation, it is useful to evaluate the alignability of the point cloud pairs prior to the registration. We propose an algorithm that predicts the alignability of two point clouds based on the minimum distances of descriptors. It calculates statistical values describing the minimum distances and classifies the point cloud pairs.
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Kirsch, André ; Günter, Andrei ; König, Matthias: Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features : Hochschule Bielefeld, 2022
Kirsch A, Günter A, König M. Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features. Hochschule Bielefeld; 2022.
Kirsch, A., Günter, A., & König, M. (2022). Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features. Hochschule Bielefeld.
@book{Kirsch_Günter_König_2022, title={Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features}, publisher={Hochschule Bielefeld}, author={Kirsch, André and Günter, Andrei and König, Matthias}, year={2022} }
Kirsch, André, Andrei Günter, and Matthias König. Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features. Hochschule Bielefeld, 2022.
A. Kirsch, A. Günter, and M. König, Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features. Hochschule Bielefeld, 2022.
Kirsch, André, et al. Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features. Hochschule Bielefeld, 2022.

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