FNS, CFNS, and HEIV: extending three vision parameter estimation methods
Date
2003
Authors
Chojnacki, W.
Brooks, M.
Van Den Hengel, A.
Gawley, D.
Editors
Sun, C.
Talbot, H.
Ourselin, S.
Adriaansen, T.
Talbot, H.
Ourselin, S.
Adriaansen, T.
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
Digital image computing : techniques and applications ; proceedings of the VIIth Biennial Australian Pattern Recognition Society Conference, DICTA 2003 / C. Sun, H. Talbot, S. Ourselin and T. Adriaansen (eds.), vol. 1, pp. 449-458
Statement of Responsibility
Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel, and Darren Gawley
Conference Name
Biennial Australian Pattern Recognition Society Conference (7th : 2003 : Sydney, NSW.)
Abstract
Estimation of parameters from image tokens is a central problem in computer vision. FNS, CFNS and HEIV are three recently developed methods for solving special but important cases of this problem. The schemes are means for finding unconstrained (FNS, HEIV) and constrained (CFNS) minimisers of cost functions. In earlier work of the authors, FNS, CFNS and a version of HEIV were applied to a specific cost function. Here we outline an extension of the approach to more general cost functions. This allows the FNS, CFNS and HEIV methods to be placed within a common framework.