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Light, camera, action and arrest

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posted on 22.04.2008, 15:04 by Iain T. Darker, Alastair Gale, Leila Ward, Anastassia Blechko, Kevin Purdy
Gun crime is a fast growing problem in the UK and it is important to detect a potential gun crime before an incident occurs. A possible technological and cost-effective approach is to utilise the widespread and endemic installation of CCTV cameras to automatically recognise individuals carrying concealed weapons and so prompt the CCTV operator. Current machine imaging software can identify a range of suspicious behaviours but with varying accuracy and associated false alarms. CCTV operators learn to identify certain cues associated with suspicious behaviour, again with varying accuracy. In a new EPSRC supported research project, MEDUSA sets out to identify both human and machine detected cues of individuals carrying concealed guns and merge these into new software for use by CCTV operators. This paper concentrates on the identification of cues associated with carrying concealed weapons and sets out the ergonomic challenges surrounding such an approach, together with the potential ways to overcome them.

History

School

  • Science

Department

  • Computer Science

Citation

DARKER, I.T. ... et al, 2007. Light, camera, action and arrest. IN: Contemporary Ergonomics 2007 : Proceedings of the International Conference on Contemporary Ergonomics (CE2007), 17-19 April 2007, Nottingham, UK, pp. 171-177

Publisher

© Taylor & Francis

Publication date

2007

Notes

This definitive version of this conference paper is available from http://www.taylorandfrancis.co.uk/

ISBN

9780415436380;0415436389

Language

en

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