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ID 14087
Eprint ID
14087
FullText URL
Author
Abstract
A rigorous accuracy analysis is given to various techniques for estimating parameters of geometric models from noisy data for computer vision applications. First, it is pointed out that parameter estimation for vision applications is very different in nature from traditional statistical analysis and hence a different mathematical framework is necessary in such a domain. After general theories on estimation and accuracy are given, typical existing techniques are selected, and their accuracy is evaluated up to higher order terms. This leads to a “hyperaccurate” method that outperforms existing methods.
Published Date
2007-01
Publication Title
Memoirs of the Faculty of Engineering, Okayama University
Volume
volume41
Issue
issue1
Publisher
Faculty of Engineering, Okayama University
Publisher Alternative
岡山大学工学部
Start Page
73
End Page
92
ISSN
0475-0071
NCID
AA10699856
Content Type
Departmental Bulletin Paper
language
英語
File Version
publisher
Refereed
False
Eprints Journal Name
mfe