Ship Landmark: An Informative Ship Image Annotation and Its Applications

Visual perception of ships has been attracting increasing attention in the fields of computer vision and ocean engineering. Despite the extensive work related to landmark detection of common objects, the role of landmarks in ship perception has been overlooked. In this paper, the authors aim to fill this gap by focusing on ship landmarks. Specifically, the authors give a comprehensive analysis of both the physical structure and deep features of ships, which finds that highlighted areas in feature maps correspond with structurally significant parts of ships. By summarizing the locations of such areas in ships, the authors define 20 ship landmarks and build the Ship Landmark Dataset (SLAD), the first ship dataset with landmark annotations. The authors also provide a benchmark for ship landmark detection by evaluating state-of-the-art landmark detection methods on the newly built SLAD. Moreover, the authors showcased several applications of ship landmarks, including ship recognition, ship image generation, key area detection for ships, and ship detection. Project web page: https://vsislab.github.io/Ships_VSIS/.

• Record URL:
  • http://dx.doi.org/10.1109/TITS.2024.3404973
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Copyright © 2024, IEEE.
• Authors:
  • Zhang, Mingxin
  • Zhang, Qian
  • Song, Ran
  • Rosin, Paul L
  • Zhang, Wei
• Publication Date: 2024-11

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 17778-17793
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 25
  • Issue Number: 11
  • 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: Computer vision; Databases; Monitoring; Ship structural components; Ships; Vehicle detectors
• Subject Areas: Data and Information Technology; Marine Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01948362
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 11 2025 5:10PM