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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shahir, H.Y. Glasser, U. Nalbandyan, N. Wehn, H. |
| Copyright Year | 2014 |
| Description | Author affiliation: R&D, MDA Syst. Ltd., Richmond, BC, Canada (Wehn, H.) || Software Technol. Lab., Simon Fraser Univ., Burnaby, BC, Canada (Shahir, H.Y.; Glasser, U.; Nalbandyan, N.) |
| Abstract | Maritime security is critical for protecting sea lanes, ports, harborsand other critical infrastructure against a broad range of threats and illegal activities like smuggling, human trafficking, piracy and terrorism. Limited resources constrain maritime domain awareness and compromise full security coverage at all times. This situation calls for innovative intelligent systems for interactive situation analysis to assist marine authorities and security personal in their routine surveillance operations. In this paper, we propose a novel situation analysis approach to analyze, detect and differentiate a range of interaction patterns and anomalies of interest for marine vessels that operate over some period of time in relative proximity to each other. We analyze vessel interaction scenarios to model common patterns as probabilistic processes in terms of hidden Markov models. To differentiate suspicious activities from unobjectionable behavior, we explore fusion of data and information from observable behavior (geospatial aspects, kinematic features and contextual information) and maritime domain knowledge from diverse sources. Our experimental evaluation using real-world vessel tracking data shows the effectiveness of the approach. |
| Starting Page | 192 |
| Ending Page | 199 |
| File Size | 654901 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9781479963645 |
| DOI | 10.1109/JISIC.2014.36 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-09-24 |
| Publisher Place | Netherlands |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Anomaly Detection Intelligent Systems Hidden Markov models Decision Support Interactive Situation Analysis Kinematics Feature extraction Cognition Maritime Safety & Security Trajectory Security Marine vehicles |
| Content Type | Text |
| Resource Type | Article |
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