Hy-Seg: A Hybrid Method for Ground Segmentation Using Point Clouds-Reference-Cited by-同舟云学术

Hy-Seg: A Hybrid Method for Ground Segmentation Using Point Clouds

Published:2023-02 Issue:2 Volume:8 Page:1597-1606
ISSN:2379-8904
Container-title:IEEE Transactions on Intelligent Vehicles
language:
Short-container-title:IEEE Trans. Intell. Veh.

Author:

Qian Yeqiang¹^ORCID,Wang Xiaoliang²^ORCID,Chen Ziqing³,Wang Chunxiang²^ORCID,Yang Ming²^ORCID

Affiliation:

1. University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China

2. Department of Automation, Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China

3. Research Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/7274857/10076483/09810973.pdf?arnumber=9810973

Reference37 articles.

1. Rigid Point Set Registration Based on Cubature Kalman Filter and Its Application in Intelligent Vehicles

2. Ground Segmentation Based on Loopy Belief Propagation for Sparse 3D Point Clouds

3. Depth Completion via Inductive Fusion of Planar LIDAR and Monocular Camera

4. Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

5. L-Shape Fitting-Based Vehicle Pose Estimation and Tracking Using 3D-LiDAR

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