Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/29524
Type: Conference paper
Title: FNS, CFNS, and HEIV: extending three vision parameter estimation methods
Author: Chojnacki, W.
Brooks, M.
Van Den Hengel, A.
Gawley, D.
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
Publisher: CSIRO Publishing
Publisher Place: Victoria, Australia
Issue Date: 2003
ISBN: 0643090398
Conference Name: Biennial Australian Pattern Recognition Society Conference (7th : 2003 : Sydney, NSW.)
Editor: Sun, C.
Talbot, H.
Ourselin, S.
Adriaansen, T.
Statement of
Responsibility: 
Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel, and Darren Gawley
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.
Description (link): http://www.sigmod.org/dblp/db/conf/dicta/dicta2003.html
Published version: http://www.cmis.csiro.au/Hugues.Talbot/dicta2003/cdrom/pdf/0449.pdf
Appears in Collections:Aurora harvest 6
Computer Science publications

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