3D Road Boundary Extraction Based on Machine Learning Strategy Using LiDAR and Image-Derived MMS Point Clouds
The precise extraction of road boundaries is an essential task to obtain road infrastructure data that can support various applications, such as maintenance, autonomous driving, vehicle navigation, and the generation of high-definition maps (HD map). Despite promising outcomes in prior studies, chal...
Main Authors: | Baris Suleymanoglu, Metin Soycan, Charles Toth |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-01-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/24/2/503 |
Similar Items
-
A Novel Framework for Road Information Extraction From Low-Cost MMS Point Clouds
by: Baris Suleymanoglu, et al.
Published: (2024-01-01) -
Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds
by: Li Yan, et al.
Published: (2016-06-01) -
Accurate Road Marking Detection from Noisy Point Clouds Acquired by Low-Cost Mobile LiDAR Systems
by: Ronghao Yang, et al.
Published: (2020-10-01) -
Real-Time Road Curb and Lane Detection for Autonomous Driving Using LiDAR Point Clouds
by: Jing Huang, et al.
Published: (2021-01-01) -
GPS trajectory-based segmentation and multi-filter-based extraction of expressway curbs and markings from mobile laser scanning data
by: Jin Wang, et al.
Published: (2018-01-01)