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Details of Grant 

EPSRC Reference: GR/M97312/01
Title: AUTOMATED ANALYSIS OF HUMAN BEHAVIOUR PATTERNS FROM SURVEILLANCE VIDEO DATA
Principal Investigator: Mirmehdi, Professor M
Other Investigators:
Troscianko, Professor T
Researcher Co-Investigators:
Project Partners:
Department: Computer Science
Organisation: University of Bristol
Scheme: Standard Research (Pre-FEC)
Starts: 10 April 2000 Ends: 09 April 2001 Value (£): 45,596
EPSRC Research Topic Classifications:
Cognitive Science Appl. in ICT Image & Vision Computing
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:  
Summary on Grant Application Form
Video surveillance of people has great social benefits, e.g. in crime prevention and reporting. Today's procedures require further automation to allow operators a better rate of detection.The aim of this project is to develop and advance computer vision techniques to automatically analyse image sequences from videos to detect criminal intention and criminal action. Initially, such behaviour will be modelled using psychophysical experiments to identify precise information in complex scenes containing information needed to make judgement and useful enough to predict what will happen next. The output of this process will be a set of motions modelling criminal activity.Detecting and tracking humans in video sequences is a difficult problem. We propose to use Active Shape Models to detect and track whole body motion and then use more localised techniques, like spatial, colour, texture and region analysis, to detect and track body parts. The models from the psychophysical stage will then be used for motion interpretation.The developed algorithms will be vigorously evaluated using ground-data from the psychophysical experiments.
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Organisation Website: http://www.bris.ac.uk