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Details of Grant 

EPSRC Reference: GR/R83811/01
Title: Surface Reconstruction from Gauss Maps
Principal Investigator: Hancock, Professor E
Other Investigators:
Wilson, Professor R McIntosh, Dr IR
Researcher Co-Investigators:
Project Partners:
Department: Computer Science
Organisation: University of York
Scheme: Standard Research (Pre-FEC)
Starts: 01 October 2002 Ends: 31 March 2006 Value (£): 182,138
EPSRC Research Topic Classifications:
Image & Vision Computing Mathematical Analysis
EPSRC Industrial Sector Classifications:
Communications
Related Grants:
Panel History:  
Summary on Grant Application Form
SummaryDescribe the proposed research in about 200 words.The proposed research aims to develop the computational and mathematical framework for reconstructing surfaces from their Guass maps. The main challenge here is to find curvature or energy minimising paths through the Gauss map. Once this path is to hand, then the height reconstruction process is a straightforward one which involves only the application of Eulers method. At York, we have already developed a computationally effective algorithm for this purpose which uses a graph-spectral characterisation based on the leading eigenvector of a curvature property matrix. The research proposed here aims to establish a mathematical framework for the process. We will commence by using stochastic geometry to pose the recovery of a curvature minimising path in a variational setting using stochastic differential equations. To apply this apparatus to the location of curvature minimising paths, we will require a probabilistic characterisation of the Gauss-maps and the site transitions undergone by the path. Finally, we will demonstrate the utility of the resulting surface reconstruction algorithms on surface normal data delivered by shape-from-shading and shape-from-texture.
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Organisation Website: http://www.york.ac.uk