Multiple point cloud registration and global consistency condition

Artyom Makovetskii; Sergei Voronin; Vitaly Kober; Aleksei Voronin; Tatyana Makovetskaya

doi:10.1117/12.2677107

4 October 2023 Multiple point cloud registration and global consistency condition

Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Aleksei Voronin, Tatyana Makovetskaya

Proceedings Volume 12674, Applications of Digital Image Processing XLVI; 126741I (2023) https://doi.org/10.1117/12.2677107
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Conference Poster

Abstract

Point cloud registration is a central problem in many mapping and monitoring applications such as 3D model reconstruction, computer vision, autonomous driving, and others. Generating maps of the environment is often referred to as the Simultaneous Localization and Mapping (SLAM) problem. Note that some point clouds from the considered set may not have intersections. In this paper, we propose an algorithm to align the multiple point clouds based on an effective pairwise registration and a global refinement algorithm. The global refinement algorithm is non-iterative. Computer simulation results are provided to illustrate the performance of the proposed method.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Aleksei Voronin, and Tatyana Makovetskaya "Multiple point cloud registration and global consistency condition", Proc. SPIE 12674, Applications of Digital Image Processing XLVI, 126741I (4 October 2023); https://doi.org/10.1117/12.2677107

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