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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/6287

Title: Automation of the CCTV-mediated detection of individuals illegally carrying firearms: combining psychological and technological approaches
Authors: Darker, Iain T.
Kuo, Paul
Yang, Ming Yuan
Blechko, Anastassia
Grecos, Christos
Makris, Dimitrios
Nebel, Jean-Christophe
Gale, Alastair G.
Keywords: CCTV
Firearm
Signal detection
Machine vision
Human performance
Automation
Issue Date: 2009
Publisher: © 2009 Society of Photo-Optical Instrumentation Engineers
Citation: DARKER, I.T. ... et al., 2009. Automation of the CCTV-mediated detection of individuals illegally carrying firearms: combining psychological and technological approaches. IN: Rahman, Z.U., Reichenbach, S.E. and Neifeld, M.A. (eds.). Visual Information Processing XVIII. Proceedings of SPIE 7341, 73410P, 9 pp.
Abstract: Findings from the current UK national research programme, MEDUSA (Multi Environment Deployable Universal Software Application), are presented. MEDUSA brings together two approaches to facilitate the design of an automatic, CCTV-based firearm detection system: psychological—to elicit strategies used by CCTV operators; and machine vision—to identify key cues derived from camera imagery. Potentially effective human- and machine-based strategies have been identified; these will form elements of the final system. The efficacies of these algorithms have been tested on staged CCTV footage in discriminating between firearms and matched distractor objects. Early results indicate the potential for this combined approach.
Description: Copyright 2009 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. This paper can also be found at: http://dx.doi.org/10.1117/12.819998
Version: Published
DOI: 10.1117/12.819998
URI: https://dspace.lboro.ac.uk/2134/6287
Appears in Collections:Conference Papers (Computer Science)

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