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Details of Grant 

EPSRC Reference: EP/D078830/1
Title: MEDUSA Multi Environment Deployable Universal Software Application
Principal Investigator: Gale, Professor AG
Other Investigators:
Grecos, Professor C
Researcher Co-Investigators:
Project Partners:
ACPO CCTV User Group Forensic Alliance Ltd
Greater Manchester Police (The) Metropolitan Police Service National Firearms Centre
Department: Ergonomics and Safety Research Institute
Organisation: Loughborough University
Scheme: Standard Research
Starts: 21 August 2006 Ends: 20 February 2010 Value (£): 398,698
EPSRC Research Topic Classifications:
Information & Knowledge Mgmt Software Engineering
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine Information Technologies
Related Grants:
EP/E001025/1 EP/D078245/1 EP/D078105/1 EP/D078326/1
Panel History:  
Summary on Grant Application Form
A key factor in reducing potential gun crime is to detect someone carrying a gun before they can commit a criminal act. This detection can be achieved by the existing, and widespread, CCTV camera network in the UK. However, the performance of operators in interpreting CCTV imagery is variable as they are trying to detect essentially a very rare threat event. Additionally, current automated systems for detecting possible anomalous behaviour have been found to have varying success. We propose the development of a new machine learning system for the detection of individuals carrying guns which will combine both human and machine-based factors. Using selected CCTV footage which depicts people carrying concealed guns, and other control individuals, the proposal will establish what overt and covert cues (essentially conscious and subconscious cues) experienced CCTV operators actually attend to when identifying potential gun-carrying individuals from such CCTV imagery. In parallel, a machine learning approach will establish the machine recognised cues for such individuals. The separate human and machine cues will then be combined to form a new machine learning approach which will be fully tested. The system will be capable of learning and reacting to local gun crime factors which will aid its usefulness and deployment capability.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Project URL: http://www.lboro.ac.uk/research/applied-vision/projects/medusa/index.htm
Further Information:  
Organisation Website: http://www.lboro.ac.uk