Paper
5 May 2009 Automated intelligent video surveillance system for ships
Hai Wei, Hieu Nguyen, Prakash Ramu, Chaitanya Raju, Xiaoqing Liu, Jacob Yadegar
Author Affiliations +
Abstract
To protect naval and commercial ships from attack by terrorists and pirates, it is important to have automatic surveillance systems able to detect, identify, track and alert the crew on small watercrafts that might pursue malicious intentions, while ruling out non-threat entities. Radar systems have limitations on the minimum detectable range and lack high-level classification power. In this paper, we present an innovative Automated Intelligent Video Surveillance System for Ships (AIVS3) as a vision-based solution for ship security. Capitalizing on advanced computer vision algorithms and practical machine learning methodologies, the developed AIVS3 is not only capable of efficiently and robustly detecting, classifying, and tracking various maritime targets, but also able to fuse heterogeneous target information to interpret scene activities, associate targets with levels of threat, and issue the corresponding alerts/recommendations to the man-in- the-loop (MITL). AIVS3 has been tested in various maritime scenarios and shown accurate and effective threat detection performance. By reducing the reliance on human eyes to monitor cluttered scenes, AIVS3 will save the manpower while increasing the accuracy in detection and identification of asymmetric attacks for ship protection.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hai Wei, Hieu Nguyen, Prakash Ramu, Chaitanya Raju, Xiaoqing Liu, and Jacob Yadegar "Automated intelligent video surveillance system for ships", Proc. SPIE 7306, Optics and Photonics in Global Homeland Security V and Biometric Technology for Human Identification VI, 73061N (5 May 2009); https://doi.org/10.1117/12.819051
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Cited by 24 scholarly publications.
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KEYWORDS
Target detection

Decision support systems

Intelligence systems

Video surveillance

Detection and tracking algorithms

Video

Visualization

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