Paper
12 May 2006 SeeCoast port surveillance
Michael Seibert, Bradley J Rhodes, Neil A. Bomberger, Patricia O Beane, Jason J Sroka, Wendy Kogel, William Kreamer, Chris Stauffer, Linda Kirschner, Edmond Chalom, Michael Bosse, Robert Tillson
Author Affiliations +
Abstract
SeeCoast extends the US Coast Guard Port Security and Monitoring system by adding capabilities to detect, classify, and track vessels using electro-optic and infrared cameras, and also uses learned normalcy models of vessel activities in order to generate alert cues for the watch-standers when anomalous behaviors occur. SeeCoast fuses the video data with radar detections and Automatic Identification System (AIS) transponder data in order to generate composite fused tracks for vessels approaching the port, as well as for vessels already in the port. Then, SeeCoast applies rule-based and learning-based pattern recognition algorithms to alert the watch-standers to unsafe, illegal, threatening, and other anomalous vessel activities. The prototype SeeCoast system has been deployed to Coast Guard sites in Virginia. This paper provides an overview of the system and outlines the lessons learned to date in applying data fusion and automated pattern recognition technology to the port security domain.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael Seibert, Bradley J Rhodes, Neil A. Bomberger, Patricia O Beane, Jason J Sroka, Wendy Kogel, William Kreamer, Chris Stauffer, Linda Kirschner, Edmond Chalom, Michael Bosse, and Robert Tillson "SeeCoast port surveillance", Proc. SPIE 6204, Photonics for Port and Harbor Security II, 62040B (12 May 2006); https://doi.org/10.1117/12.666980
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CITATIONS
Cited by 37 scholarly publications and 1 patent.
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KEYWORDS
Cameras

Video

Video processing

Radar

Video surveillance

Artificial intelligence

Data modeling

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