Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Type: Conference paper
Title: FNS and HEIV: relating two vision parameter estimation frameworks
Author: Chojnacki, W.
Brooks, M.
Van Den Hengel, A.
Gawley, D.
Citation: Proceedings, 12th International Conference on Image Analysis and Processing : Mantova, Italy, September 17 to 19, 2003 / pp. 152-157
Publisher: IEEE
Publisher Place: California, USA
Issue Date: 2003
ISBN: 0769519482
Conference Name: International Conference on Image Analysis and Processing (12th : 2003 : Mantova, Italy)
Editor: Feretti, M.
Statement of
Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel, Darren Gawley
Abstract: Problems requiring accurate determination of parameters from image-based quantities arise often in computer vision. Two recent, independently developed frameworks for estimating such parameters are the FNS and HEIV schemes. Here it is shown that FNS and a core version of HEIV are essentially equivalent, solving a common underlying equation via different means. The analysis is driven by the search for a non-degenerate form of a certain generalised eigen-value problem, and effectively leads to a new derivation of the relevant case of the HEIV algorithm. This work may be seen as an extension of previous efforts to rationalise and inter-relate a spectrum of estimators, including the renormalisation method of Kanatani and the normalised eight-point method of Hartley.
Description: ©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
DOI: 10.1109/ICIAP.2003.1234042
Published version:
Appears in Collections:Aurora harvest 2
Computer Science publications

Files in This Item:
File Description SizeFormat 
hdl_29522.pdf205.98 kBPublisher's PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.