Title
Recognition of ships for long-term tracking
Author
van den Broek, S.P.
Bouma, H.
Veerman, H.E.T.
Benoist, K.W.
den Hollander, R.J.M.
Schwering, P.B.W.
Contributor
Kadar, I. (editor)
Publication year
2014
Abstract
Long-term tracking is important for maritime situational awareness to identify currently observed ships as earlier encounters. In cases of, for example, piracy and smuggling, past location and behavior analysis are useful to determine whether a ship is of interest. Furthermore, it is beneficial to make this assessment with sensors (such as cameras) at a distance, to avoid costs of bringing an own asset closer to the ship for verification. The emphasis of the research presented in this paper, is on the use of several feature extraction and matching methods for recognizing ships from electro-optical imagery within different categories of vessels. We compared central moments, SIFT with localization and SIFT with Fisher Vectors. From the evaluation on imagery of ships, an indication of discriminative power is obtained between and within different categories of ships. This is used to assess the usefulness in persistent tracking, from short intervals (track improvement) to larger intervals (re-identifying ships). The result of this assessment on real data is used in a simulation environment to determine how track continuity is improved. The simulations showed that even limited recognition will improve tracking, connecting both tracks at short intervals as well as over several days. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Subject
TS - Technical Sciences
Physics & Electronics
Defence, Safety and Security
Defence Research
Track recognition
Persistent tracking
Maritime environment
Situational awareness
Electro-optical
Infrared
Ships
II - Intelligent Imaging ; ED - Electronic Defence
To reference this document use:
http://resolver.tudelft.nl/uuid:a1e0ecc2-1791-4bfe-942d-986fdad97a5f
DOI
https://doi.org/10.1117/12.2053295
TNO identifier
505068
Publisher
SPIE, Bellingham, WA
Source
Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII, 5 May 2014, Baltimore, MD, USA
Series
Proceedings SPIE
Document type
conference paper