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CCTV as an automated sensor for firearms detection: human-derived performance as a precursor to automatic recognition

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conference contribution
posted on 03.06.2010, 10:10 by Iain T. Darker, Alastair Gale, Anastassia Blechko
CCTV operators are able to detect firearms, via CCTV, but their capacity for surveillance is limited. Thus, it is desirable to automate the monitoring of CCTV cameras for firearms using machine vision techniques. The abilities of CCTV operators to detect concealed and unconcealed firearms in CCTV footage were quantified within a signal detection framework. Additionally, the visual search strategies adopted by the CCTV operators were elicited and their efficacies indexed with respect to signal detection performance, separately for concealed and unconcealed firearms. Future work will automate effective, human visual search strategies using image processing algorithms.

History

School

  • Science

Department

  • Computer Science

Citation

DARKER, I.T., GALE, A.G. and BLECHKO, A., 2008. CCTV as an automated sensor for firearms detection: human-derived performance as a precursor to automatic recognition. IN: Carapezza, E.M. (ed.). Unmanned/Unattended Sensors and Sensor Networks V, Proceedings of SPIE 7112, 71120V, 12 pp.

Publisher

© 2008 Society of Photo-Optical Instrumentation Engineers

Version

VoR (Version of Record)

Publication date

2008

Notes

Copyright 2008 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/10.1117/12.800264

Language

en