Are Object Detection Assessment Criteria Ready for Maritime Computer Vision?

Maritime vessels equipped with visible and infrared cameras can complement other conventional sensors for object detection. However, application of computer vision techniques in maritime domain received attention only recently. The maritime environment offers its own unique requirements and challenges. Assessment of the quality of detections is a fundamental need in computer vision. However, the conventional assessment metrics suitable for usual object detection are deficient in the maritime setting. Thus, a large body of related work in computer vision appears inapplicable to the maritime setting at the first sight. The authors discuss the problem of defining assessment metrics suitable for maritime computer vision. They consider new bottom edge proximity metrics as assessment metrics for maritime computer vision. These metrics indicate that existing computer vision approaches are indeed promising for maritime computer vision and can play a foundational role in the emerging field of maritime computer vision.

• Record URL:
  • https://doi.org/10.1109/TITS.2019.2954464
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Copyright © 2020, IEEE.
• Authors:
  • Prasad, Dilip K
  • Dong, Huixu
  • Rajan, Deepu
  • Quek, Chai
• Publication Date: 2020-12

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 5295-5304
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 21
  • Issue Number: 12
  • 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: Cameras; Computer vision; Detection and identification systems; Intelligent vehicles; Maritime safety; Neural networks; Ships; Visual texture recognition
• Subject Areas: Marine Transportation; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01761885
• Record Type: Publication
• Files: TLIB, TRIS
• Created Date: Dec 31 2020 4:59PM