Urban road scenes utilize lightweight fast point cloud auto-registration of poles-like and lane lines

Huiyou ZHAO; Xuequn WU; Yonghua Xia

doi:10.37188/ope.20243204.0535

ScienceGate Book Chapters

JOURNAL ARTICLE

Urban road scenes utilize lightweight fast point cloud auto-registration of poles-like and lane lines

Huiyou ZHAO Xuequn WU Yonghua Xia

Year: 2024 Journal: Optics and Precision Engineering Vol: 32 (4)Pages: 535-548

DOI: 10.37188/ope.20243204.0535

Get Full-Text PDF Get Analytical Report

Keywords:

Point cloud Cloud computing Computer science Point (geometry) Computer graphics (images) Computer vision Artificial intelligence Transport engineering Engineering Mathematics Geometry Operating system

Metrics

Cited By

0.40

FWCI (Field Weighted Citation Impact)

Refs

0.46

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Autonomous Vehicle Technology and Safety

Physical Sciences → Engineering → Automotive Engineering

Remote Sensing and LiDAR Applications

Physical Sciences → Environmental Science → Environmental Engineering

Computer Graphics and Visualization Techniques

Physical Sciences → Computer Science → Computer Graphics and Computer-Aided Design

Urban road scenes utilize lightweight fast point cloud auto-registration of poles-like and lane lines

Metrics

Citation History

Topics

Related Documents

Fast Point Cloud Registration for Urban Scenes via Pillar-Point Representation

DDRNet: Fast point cloud registration network for large-scale scenes

PCRMLP: A Two-Stage Network for Point Cloud Registration in Urban Scenes

DeepMatch: Toward Lightweight in Point Cloud Registration

Fast Point Cloud Registration using Semantic Segmentation