Ship landmark: An informative ship image annotation and its applications

Zhang, Mingxin, Zhang, Qian, Song, Ran, Rosin, Paul L. ORCID: https://orcid.org/0000-0002-4965-3884 and Zhang, Wei 2024. Ship landmark: An informative ship image annotation and its applications. IEEE Transactions on Intelligent Transportation Systems 10.1109/TITS.2024.3404973

Preview

PDF - Accepted Post-Print Version Download (4MB) | Preview

Abstract

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, we aim to fill this gap by focusing on ship landmarks. Specifically, we 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, we define 20 ship landmarks and build the Ship Landmark Dataset (SLAD), the first ship dataset with landmark annotations. We also provide a benchmark for ship landmark detection by evaluating state-of-the-art landmark detection methods on the newly built SLAD. Moreover, we showcased several applications of ship landmarks, including ship recognition, ship image generation, key area detection for ships, and ship detection.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Computer Science & Informatics
Publisher:	Institute of Electrical and Electronics Engineers
ISSN:	1524-9050
Date of First Compliant Deposit:	24 June 2024
Date of Acceptance:	20 May 2024
Last Modified:	09 Nov 2024 18:45
URI:	https://orca.cardiff.ac.uk/id/eprint/169568

Actions (repository staff only)

Edit Item