A Fast Ground Segmentation Method of LiDAR Point Cloud From Coarse-to-Fine
Author:
Affiliation:
1. National Key Laboratory of Tunable Laser Technology, Harbin Institute of Technology, Harbin, China
2. Department of Microwave Engineering, School of Electronic and Information Engineering, Harbin Institute of Technology, Harbin, China
Funder
National Key Scientific Instrument and Equipment Development Projects of China
Shenzhen Fundamental Research Program
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10017147/09969541.pdf?arnumber=9969541
Reference27 articles.
1. Fast segmentation of 3D point clouds for ground vehicles
2. Fast segmentation of 3D point clouds: A paradigm on LiDAR data for autonomous vehicle applications
3. A Fast Point Cloud Ground Segmentation Approach Based on Coarse-To-Fine Markov Random Field
4. A Slope-robust Cascaded Ground Segmentation in 3D Point Cloud for Autonomous Vehicles
5. Gaussian-Process-Based Real-Time Ground Segmentation for Autonomous Land Vehicles
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1. An efficient ground segmentation approach for LiDAR point cloud utilizing adjacent grids;Machine Vision and Applications;2024-08-11
2. Multisensor Fusion Network for Unstructured Scene Segmentation With Surface Normal Incorporated;IEEE Sensors Journal;2024-04-15
3. A Staged Real-Time Ground Segmentation Algorithm of 3D LiDAR Point Cloud;Electronics;2024-02-22
4. Velocity Estimation for Space Infrared Dim Targets Based on Multi-Satellite Observation and Robust Locally Weighted Regression;Remote Sensing;2023-05-26
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