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Details of Grant 

EPSRC Reference: GR/M36182/01
Title: PERCEPTION AND CLASSIFICATION OF VISUAL MOTION
Principal Investigator: Zisserman, Professor A
Other Investigators:
Noble, Professor A Noble, Dr A
Researcher Co-Investigators:
Project Partners:
Department: Engineering Science
Organisation: University of Oxford
Scheme: Standard Research (Pre-FEC)
Starts: 21 June 1999 Ends: 20 March 2003 Value (£): 212,461
EPSRC Research Topic Classifications:
Image & Vision Computing
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:  
Summary on Grant Application Form
The proposal is to develop a probabilistic framework for perception (or estimation) and classification of complex time-varying signals, represented as temporal streams of states. This has many applications including, but not restricted to, classification of visual motion. The theoretical focus of the proposal addresses both machine-perception and learning. Algorithms for perception ( condensation or particle filtering ) based on random generation of sets of samples are proving very successful. The aim is to develop a particle-filter that deals simultaneously with several different classes of motion (e.g. walk-trot-cantor-gallop). This would then be combined with Bayesian smoothing and a form of Expectation Maximisation (EM) algorithm expressed in terms of particle sets. This is the starting point for a whole series of estimation and learning studies as detailed in the research programme. Tests of efficiency of the new algorithms would be carried out in the context of surveillance, where Visual Motion Detection (VMD) is required to be selective for threateningmotions and in the discrimination of gestures in a user interface.
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Organisation Website: http://www.ox.ac.uk