Automatic Maritime Surveillance with Visual Target Detection

In this paper an automatic maritime surveillance system is presented. Boat detection is performed by means of an Haar-like classifier in order to obtain robustness with respect to targets having very different size, reflections and wakes on the water surface, and apparently motionless boats anchored off the coast. Detection results are filtered over the time in order to reduce the false alarm rate. Experimental results show the effectiveness of the approach with different light conditions and camera positions. The system is able to provide the user a global view adding a visual dimension to AIS data.

[1]  Gary Bradski,et al.  Computer Vision Face Tracking For Use in a Perceptual User Interface , 1998 .

[2]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[3]  Mubarak Shah,et al.  Visual surveillance in maritime port facilities , 2008, SPIE Defense + Commercial Sensing.

[4]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[5]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[6]  Dmitry B. Goldgof,et al.  Tracking Ships from Fast Moving Camera through Image Registration , 2010, 2010 20th International Conference on Pattern Recognition.

[7]  Rob G. J. Wijnhoven,et al.  Online learning for ship detection in maritime surveillance , 2010 .

[8]  Fatih Murat Porikli,et al.  Pedestrian Detection via Classification on Riemannian Manifolds , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  B.J. Rhodes,et al.  SeeCoast: Automated Port Scene Understanding Facilitated by Normalcy Learning , 2006, MILCOM 2006 - 2006 IEEE Military Communications conference.

[10]  Luca Iocchi,et al.  Argos - a Video Surveillance System for boat Traffic Monitoring in Venice , 2009, Int. J. Pattern Recognit. Artif. Intell..

[11]  Michele Fiorini,et al.  Fully solid state radar for vessel traffic services , 2010, 11-th INTERNATIONAL RADAR SYMPOSIUM.

[12]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.