| EPSRC Reference: |
GR/N09770/01 |
| Title: |
ICONS: INCIDENT RECOGNITION FOR SURVEILLANCE AND SECURITY |
| Principal Investigator: |
Gong, Professor S |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Computer Science |
| Organisation: |
Queen Mary University of London |
| Scheme: |
LINK |
| Starts: |
13 July 2000 |
Ends: |
12 December 2003 |
Value (£): |
289,453
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Image & Vision Computing |
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| EPSRC Industrial Sector Classifications: |
| Aerospace, Defence and Marine |
Creative Industries |
| Retail |
No relevance to Underpinning Sectors |
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| Panel History: |
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Summary on Grant Application Form |
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This project will further develop existing algorithms to specifically address two areas relevant to the processing, interpreation and management of large quantities of visual information captured by live CCTV cameras: Zero-Motion Incident Detection and Abnormal Behaviour Recognition. The proposed work is based on extensive research foundation established at QMW over the last ten years, including work carried out under two EPSRC projects, one European EPSRC II project and one European HCM network. Whilst the proposed research is relevant to and can benefit from other ongoing work at QMW such as face and gesture recognition, it addresses significantly different problems. The algorithms developed will greatly extend the capabilities of existing surveillance techniques that are already widely adopted by commercial and government security systems dedicated to the safeguarding of people, valuables, and sensitive areas.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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