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Details of Grant 

EPSRC Reference: GR/S98443/01
Title: REVEAL - Recovering Evidence from Video by Fusing Video Evidence Thesaurus & Video Meta-Data
Principal Investigator: Jones, Professor G
Other Investigators:
Ellis, Professor TJ Makris, Professor D
Researcher Co-Investigators:
Project Partners:
Crowd Dynamics Ltd Ipsotek Ltd Overview Ltd
Police Information Technology Org. Police Scientific Development Branch
Department: Faculty of Computing Info System & Maths
Organisation: Kingston University
Scheme: Standard Research (Pre-FEC)
Starts: 01 September 2004 Ends: 31 May 2008 Value (£): 208,894
EPSRC Research Topic Classifications:
Image & Vision Computing
EPSRC Industrial Sector Classifications:
Creative Industries
Related Grants:
GR/S98467/01 GR/S98450/01
Panel History:  
Summary on Grant Application Form
During any major crime investigation, the establishment of the identity of vehicles and individuals involved in crime incidents necessitates the extremely time-consuming process of manually annotating all available CCTV tapes and digital archives. Therefore, any technology for recovering intelligence automatically from video footage must be a priority for development of the evidence-gathering capability of our Police Forces. This project aims to advance research in the recovery of evidence from video footage. There are two key crime-oriented applications that will directly benefit from this research. First, video summarisation of CCTV archives i.e. the automatic gen-eration of a gallery of mug-shots and numberplates for all moving objects. Such a gallery represents the most ef-fective method of enlisting the knowledge of local police officers and the general public. Second, automatic annotation of video footage to ensure all evidence should be capable of automatic entry into HOLMES 2 - the in-vestigation management system used by police forces to collect, manage and analyse intelligence data.Two novel areas of investigation are proposed. First, methods for representing and analysing crowds are to be de-veloped to process typically crowded scenes. Second, multi-modal data fusion couples the linguistic structure of current police annotation practice with the meta-data structure of the video interpretation process to generate a rich homogenous data representation that can drive the annotation process.
Key Findings
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Project URL:  
Further Information:  
Organisation Website: http://www.kingston.ac.uk