FNS, CFNS and HEIV: A Unifying Approach

Authors:
Wojciech Chojnacki;Michael J. Brooks;Anton Hengel;Darren Gawley
Affiliations:
School of Computer Science, University of Adelaide, Adelaide, Australia 5005;School of Computer Science, University of Adelaide, Adelaide, Australia 5005;School of Computer Science, University of Adelaide, Adelaide, Australia 5005;School of Computer Science, University of Adelaide, Adelaide, Australia 5005
Venue:
Journal of Mathematical Imaging and Vision
Year:
2005

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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 core version of HEIV were applied to a specific cost function. Here we extend the approach to more general cost functions. This allows the FNS, CFNS and HEIV methods to be placed within a common framework.