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Real-Time Road Intersection Detection in Sparse Point Cloud Based on Augmented Viewpoints Beam Model

Road intersection is a kind of important navigation landmark, while existing detection methods exhibit clear limitations in terms of their robustness and efficiency. A real-time algorithm for road intersection detection and location in large-scale sparse point clouds is proposed in this paper. Diffe...

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Detalles Bibliográficos
Autores principales: Hu, Di, Zhang, Kai, Yuan, Xia, Xu, Jiachen, Zhong, Yipan, Zhao, Chunxia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650652/
https://www.ncbi.nlm.nih.gov/pubmed/37960553
http://dx.doi.org/10.3390/s23218854
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author Hu, Di
Zhang, Kai
Yuan, Xia
Xu, Jiachen
Zhong, Yipan
Zhao, Chunxia
author_facet Hu, Di
Zhang, Kai
Yuan, Xia
Xu, Jiachen
Zhong, Yipan
Zhao, Chunxia
author_sort Hu, Di
collection PubMed
description Road intersection is a kind of important navigation landmark, while existing detection methods exhibit clear limitations in terms of their robustness and efficiency. A real-time algorithm for road intersection detection and location in large-scale sparse point clouds is proposed in this paper. Different from traditional approaches, our method establishes the augmented viewpoints beam model to perceive the road bifurcation structure. Explicitly, the spatial features from point clouds are jointly extracted in various viewpoints in front of the robot. In addition, the evaluation metrics are designed to self-assess the quality of detection results, enabling our method to optimize the detection process in real time. Considering the scarcity of datasets for intersection detection, we also collect and annotate a VLP-16 point cloud dataset specifically for intersections, called NCP-Intersection. Quantitative and qualitative experiments demonstrate that the proposed method performs favorably against the other parallel methods. Specifically, our method performs an average precision exceeding 90% and an average processing time of approximately 88 ms/frame.
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spelling pubmed-106506522023-10-31 Real-Time Road Intersection Detection in Sparse Point Cloud Based on Augmented Viewpoints Beam Model Hu, Di Zhang, Kai Yuan, Xia Xu, Jiachen Zhong, Yipan Zhao, Chunxia Sensors (Basel) Article Road intersection is a kind of important navigation landmark, while existing detection methods exhibit clear limitations in terms of their robustness and efficiency. A real-time algorithm for road intersection detection and location in large-scale sparse point clouds is proposed in this paper. Different from traditional approaches, our method establishes the augmented viewpoints beam model to perceive the road bifurcation structure. Explicitly, the spatial features from point clouds are jointly extracted in various viewpoints in front of the robot. In addition, the evaluation metrics are designed to self-assess the quality of detection results, enabling our method to optimize the detection process in real time. Considering the scarcity of datasets for intersection detection, we also collect and annotate a VLP-16 point cloud dataset specifically for intersections, called NCP-Intersection. Quantitative and qualitative experiments demonstrate that the proposed method performs favorably against the other parallel methods. Specifically, our method performs an average precision exceeding 90% and an average processing time of approximately 88 ms/frame. MDPI 2023-10-31 /pmc/articles/PMC10650652/ /pubmed/37960553 http://dx.doi.org/10.3390/s23218854 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hu, Di
Zhang, Kai
Yuan, Xia
Xu, Jiachen
Zhong, Yipan
Zhao, Chunxia
Real-Time Road Intersection Detection in Sparse Point Cloud Based on Augmented Viewpoints Beam Model
title Real-Time Road Intersection Detection in Sparse Point Cloud Based on Augmented Viewpoints Beam Model
title_full Real-Time Road Intersection Detection in Sparse Point Cloud Based on Augmented Viewpoints Beam Model
title_fullStr Real-Time Road Intersection Detection in Sparse Point Cloud Based on Augmented Viewpoints Beam Model
title_full_unstemmed Real-Time Road Intersection Detection in Sparse Point Cloud Based on Augmented Viewpoints Beam Model
title_short Real-Time Road Intersection Detection in Sparse Point Cloud Based on Augmented Viewpoints Beam Model
title_sort real-time road intersection detection in sparse point cloud based on augmented viewpoints beam model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650652/
https://www.ncbi.nlm.nih.gov/pubmed/37960553
http://dx.doi.org/10.3390/s23218854
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