Efficient and Accurate Method of Point Cloud Registration Based on Plane Correspondences for Structured Scenes

Registration of point clouds is a crucial process in the domain of Light Detection and Ranging (LiDAR). To enhance both efficiency and accuracy in registering point clouds in structured scenes, this paper proposes a registration method based on plane correspondences by enhancing the performance of p...

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Bibliographic Details
Published in2023 International Conference on Ubiquitous Communication (Ucom) pp. 215 - 220
Main Authors Weng, Hongyi, Qiao, Yaojun, Yang, Aiying
Format Conference Proceeding
LanguageEnglish
Published IEEE 07.07.2023
Subjects
Feature extraction
Filtering
Filtering algorithms
Laser radar
LiDAR
Matched filters
plane correspondences
plane extraction
Point cloud compression
point cloud registration
Stairs
structured scenes
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Summary:Registration of point clouds is a crucial process in the domain of Light Detection and Ranging (LiDAR). To enhance both efficiency and accuracy in registering point clouds in structured scenes, this paper proposes a registration method based on plane correspondences by enhancing the performance of plane extraction and plane matching without initial guesses from odometry or LiDAR. The proposed registration method defines a novel planar feature descriptor based on the distribution and number of points to improve the plane extraction module, effectively filtering out extraneous planes. Furthermore, a novel angular feature descriptor based on geometric information and the planar feature descriptor, are incorporated to enhance the accuracy of the plane matching, in addition to the traditional feature descriptor. The results obtained from the experiments indicate that the proposed registration method outperforms other existing algorithms, achieving success rates of 98%, 97%, and 100% on the Apartment, ETH, and Stairs datasets, respectively.
DOI:10.1109/Ucom59132.2023.10257616