High-Precision Motion Detection and Tracking Based on Point Cloud Registration and Radius Search
Detecting and tracking dynamic objects in a scene using point cloud data collected by LiDAR and estimating the motion state of objects with high accuracy are challenges for autonomous driving technology. In this study, a motion detection method based on point cloud registration is investigated to detect motion through the overlapping relationship between source and target point clouds after registration and extract moving objects using clustering and scale analysis by combining the object information of interest acquired by deep learning networks. Next, object association is achieved by object motion information and geometric and texture features. Then, a point cloud registration method flow is designed to estimate the motion state of the object with high accuracy by point cloud registration. The detection, tracking and estimation of the accurate motion state of moving objects are achieved.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
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Supplemental Notes:
- Copyright © 2023, IEEE.
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Authors:
- Li, Jianwei
- Huang, Xin
- Zhan, Jiawang
- Publication Date: 2023-6
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 6322-6335
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Serial:
- IEEE Transactions on Intelligent Transportation Systems
- Volume: 24
- Issue Number: 6
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 1524-9050
- Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Detection and identification systems; Laser radar; Machine learning; Moving target indicators; Tracking systems
- Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01897031
- Record Type: Publication
- Files: TRIS
- Created Date: Oct 23 2023 3:09PM