Abstract
Since 9/11 naval structures and facilities have been recognized as potential critical targets of terrorist acts. Consequently, harbour protection has become a debated topic due to the difficulties inherent in safeguarding such a complex environment. In this paper we will discuss an automatic multi sensor surveillance system designed to detect suspicious events in the harbour area and focus the attention of a remote human operator. Using colour and infrared cameras, the system is able to detect if someone is trying to cross an unauthorized area or if a person or vehicle performs an anomalous pattern of activity. This automatic surveillance system aims to supersede classical CCTV systems by providing effective assistance to the human operator by invoking his attention only when needed. The system can also be used to automatically tag and annotate video streams in order to perform a posteriori automatic query-based retrieval of desired events.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Balckman SS. 1986. Multiple-Target Tracking with Radar Applications. Artech House, Boston, MA.
Bar-Shalom Y, Li X. 1995. Multitarget-Multisensor Tracking: Principles and Techniques. YBS Publishing, Storrs, CT.
Collins RT, Lipton AJ, Fujiyoshi H, Kanade T. 2001. Special Section on Video Surveillance. IEEE Transactions of Pattern Analysis and Machine Intelligence. Vol. 22, n. 8.
Collins RT, Lipton AJ, Fujiyoshi H, Kanade T. 2001. A System for Video Surveillance and Monitoring. In: Proceedings of the IEEE. Vol. 89, pp. 1456–1477.
Comaniciu D, Ramesh V, Meer P. 2003. Kernel-Based Object Tracking. In: IEEE Transactions on Pattern Analysis Machine Intelligence. Vol. 25, pp. 564–575.
Foresti GL. 1999. Object Recognition and Tracking for Remote Video Surveillance. IEEE Transaction on Circuits and Systems for Video Technology. Vol. 9, n. 7, pp. 1045–1062.
Foresti GL, Regazzoni CS, Varshney PK. 2003. Multisensor Surveillance Systems: The Fusion Perspective. Kluwer, Boston, MA.
Foresti GL, Micheloni C, Snidaro L, Remagnino P, Ellis T. 2005. Active Video-Based Surveillance System. IEEE Signal Processing Magazine. Vol. 22, n. 2, pp. 25–37.
Foresti GL, Micheloni C, Snidaro L. 2002. Adaptive high order neural trees for pattern recognition. In: Proceedings of the International Conference on Pattern Recognition (ICPR). Quebec City, Vol. 2, pp. 877–880.
Johnson N, Hogg D. 1996. Learning the Distribution of Object Trajectories for Event Recognition. Image and Vision Computing, Vol. 14, n. 8, pp. 609–615.
Medioni G, Cohen I, Bremond F, Hongeng S, Nevatia R. 2001. Event Detection and Analysis from Video Streams. IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 23, no. 8, pp. 873–889.
Piciarelli C, Foresti GL. 2005. Toward Event Detection Using Dynamic Trajectory Analysis and Prediction. IEEE International Symposium on Imaging for Crime Detection and Prevention (ICDP 2005). London, pp. 131–134.
Poore AB. 1994. Multi-Dimensional Assignment Formulation of Data Association Problems Arising from Multi-Target and Multi-Sensor Tracking. In: Computational Optimization and Applications. Vol. 3, pp. 27–57.
Yilmaz A, Javed O, Shah M. 2006. Object Tracking: A Survey. In: ACM Computing Surveys. Vol. 38, n. 4, pp. 1–45.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Science + Business Media B.V.
About this paper
Cite this paper
Snidaro, L., Foresti, G.L., Piciarelli, C. (2009). Automatic Video Surveillance of Harbour Structures. In: Shahbazian, E., Rogova, G., DeWeert, M.J. (eds) Harbour Protection Through Data Fusion Technologies. NATO Science for Peace and Security Series C: Environmental Security. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8883-4_27
Download citation
DOI: https://doi.org/10.1007/978-1-4020-8883-4_27
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-8882-7
Online ISBN: 978-1-4020-8883-4
eBook Packages: Computer ScienceComputer Science (R0)