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From FNS to HEIV: a link between two vision parameter estimation methods.

作者信息

Chojnacki Wojciech, Brooks Michael J, van den Hengel Anton, Gawley Darren

机构信息

School of Computer Science, University of Adelaide, SA 5005, Australia.

出版信息

IEEE Trans Pattern Anal Mach Intell. 2004 Feb;26(2):264-8. doi: 10.1109/tpami.2004.1262197.

DOI:10.1109/tpami.2004.1262197
PMID:15376901
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 nondegenerate form of a certain generalized eigenvalue 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 rationalize and interrelate a spectrum of estimators, including the renormalization method of Kanatani and the normalized eight-point method of Hartley.

摘要

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