We introduce a circle rolling method (CRM) for boundary extraction from 2D point clouds. The core idea is to create a circle that performs pure rolling on the perimeter of the point cloud to obtain the boundary. For a 3D point cloud, a plane adsorbs points on both sides to create a 2D point cloud, and the CRM is used to extract the boundary points and map them back into space to obtain 3D boundary points. Continuously moving this plane can obtain a complete boundary, which is called the moving adsorption rolling method (MARM). In this paper, we solve the interference problems in our method caused by unidirectional overlapping points and porous structures and successfully validate the solutions in practical examples. Our point cloud boundary extraction method is faster in 2D and better for surface concavities extracted in 3D compared to existing methods, and it is unaffected by sparse points within the point cloud.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.3390/s25010045 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A 6D Object Pose Estimation Algorithm for Autonomous Docking with Improved Maximal Cliques.
Sensors (Basel)
January 2025
Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China.
Accurate 6D object pose estimation is critical for autonomous docking. To address the inefficiencies and inaccuracies associated with maximal cliques-based pose estimation methods, we propose a fast 6D pose estimation algorithm that integrates feature space and space compatibility constraints. The algorithm reduces the graph size by employing Laplacian filtering to resample high-frequency signal nodes.
View Article and Find Full Text PDFAn Autonomous Positioning Method for Drones in GNSS Denial Scenarios Driven by Real-Scene 3D Models.
Sensors (Basel)
January 2025
College of Electronics and Information Engineering, South-Central Minzu University, Wuhan 430074, China.
Drones are extensively utilized in both military and social development processes. Eliminating the reliance of drone positioning systems on GNSS and enhancing the accuracy of the positioning systems is of significant research value. This paper presents a novel approach that employs a real-scene 3D model and image point cloud reconstruction technology for the autonomous positioning of drones and attains high positioning accuracy.
View Article and Find Full Text PDFHierarchical Optimization Segmentation and Parameter Extraction of Street Trees Based on Topology Checking and Boundary Analysis from LiDAR Point Clouds.
Sensors (Basel)
January 2025
School of Geosciences, Yangtze University, Wuhan 430100, China.
Roadside tree segmentation and parameter extraction play an essential role in completing the virtual simulation of road scenes. Point cloud data of roadside trees collected by LiDAR provide important data support for achieving assisted autonomous driving. Due to the interference from trees and other ground objects in street scenes caused by mobile laser scanning, there may be a small number of missing points in the roadside tree point cloud, which makes it familiar for under-segmentation and over-segmentation phenomena to occur in the roadside tree segmentation process.
View Article and Find Full Text PDFA Secure Data Sharing Model Utilizing Attribute-Based Signcryption in Blockchain Technology.
Sensors (Basel)
December 2024
College of Cryptography Engineering, Engineering University of PAP, Xi'an 710086, China.
With the rapid development of the Internet of Things (IoT), the scope of personal data sharing has significantly increased, enhancing convenience in daily life and optimizing resource management. However, this also poses challenges related to data privacy breaches and holdership threats. Typically, blockchain technology and cloud storage provide effective solutions.
View Article and Find Full Text PDFThe Circle Pure Rolling Method for Point Cloud Boundary Extraction.
Sensors (Basel)
December 2024
Facility Design and Instrumentation Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China.
We introduce a circle rolling method (CRM) for boundary extraction from 2D point clouds. The core idea is to create a circle that performs pure rolling on the perimeter of the point cloud to obtain the boundary. For a 3D point cloud, a plane adsorbs points on both sides to create a 2D point cloud, and the CRM is used to extract the boundary points and map them back into space to obtain 3D boundary points.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!