Accessibility navigation

The SAFEE on-board threat detection system

Carter, N.L. and Ferryman, J.M. (2008) The SAFEE on-board threat detection system. In: Gasteratos, A., Vincze, M. and Tsotsos, J. K. (eds.) Computer vision systems, proceedings. Lecture Notes in Computer Science, 5008. Springer-Verlag Berlin, Berlin, pp. 79-88. ISBN 9783540795469

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.


Under the framework of the European Union Funded SAFEE project(1), this paper gives an overview of a novel monitoring and scene analysis system developed for use onboard aircraft in spatially constrained environments. The techniques discussed herein aim to warn on-board crew about pre-determined indicators of threat intent (such as running or shouting in the cabin), as elicited from industry and security experts. The subject matter experts believe that activities such as these are strong indicators of the beginnings of undesirable chains of events or scenarios, which should not be allowed to develop aboard aircraft. This project aimes to detect these scenarios and provide advice to the crew. These events may involve unruly passengers or be indicative of the precursors to terrorist threats. With a state of the art tracking system using homography intersections of motion images, and probability based Petri nets for scene understanding, the SAFEE behavioural analysis system automatically assesses the output from multiple intelligent sensors, and creates. recommendations that are presented to the crew using an integrated airborn user interface. Evaluation of the system is conducted within a full size aircraft mockup, and experimental results are presented, showing that the SAFEE system is well suited to monitoring people in confined environments, and that meaningful and instructive output regarding human actions can be derived from the sensor network within the cabin.

Item Type:Book or Report Section
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:14374
Uncontrolled Keywords:scene recognition, tracking, planar homographies
Publisher:Springer-Verlag Berlin

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation