Automated 3D Road Boundary Extraction and Vectorization Using MLS Point Clouds

To meet the urgent demands in a wide range of geospatial applications, such as road management, intelligent transportation systems, road safety evaluation, and traffic accident analysis, automatic and accurate extraction of 3D roads and associated geometric parameters from point clouds is receiving wide attention. In this paper, the authors propose an accurate 3D road boundary extraction and vectorization method to bridge the gap from unstructured mobile laser scanning (MLS) point clouds to the vector-based representation of road boundary. Firstly, they propose a supervoxel generation method to extract candidate curbs with fine border preservation and high computation efficiencies. Then the candidate curb supervoxels are recognized and clustered to produce continuous road boundary segments with a contracted distance clustering strategy. Finally, the vectorized road boundary is represented by fitting, tracking, and completion from the extracted road boundary segments, resulting in road geometric parameters including boundary location, road widths, turning radius, and slopes. The performance of the proposed method was evaluated on two large-scale datasets collected in urban and industrial areas. Comprehensive experiments reveal that the proposed method is robust to various road shapes and point densities, in terms of precision of 95.0% and recall of 91.0%, respectively.

• Record URL:
  • https://doi.org/10.1109/TITS.2021.3052882
• Record URL:
  • https://ieeexplore.ieee.org/document/9339878
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Copyright © 2022, IEEE.
• Authors:
  • Mi, Xiaoxin
  • Yang, Bisheng
  • Dong, Zhen
  • Chen, Chi
  • Gu, Jianxiang
• Publication Date: 2022-6

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 5287-5297
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 23
  • 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: Detection and identification; Image processing; Morphology; Roads; Three dimensional displays; Topology; Traffic engineering
• Subject Areas: Data and Information Technology; Highways;

Filing Info

• Accession Number: 01852080
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 21 2022 11:30AM