FNS, CFNS and HEIV: Extending Three Vision Parameter Estimation Methods

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.

• Type: Conference
• Year: 2003
• Where: DICTA
• Authors: Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel, Darren Gawley
• Keywords: Cost Functions, DICTA 2003, DICTA 2007, General Cost Functions, Specific Cost Function