ID | 14087 |
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Sort Key | 8
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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.
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Publication Title |
Memoirs of the Faculty of Engineering, Okayama University
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Published Date | 2007-01
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Volume | volume41
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Issue | issue1
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Publisher | Faculty of Engineering, Okayama University
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Publisher Alternative | 岡山大学工学部
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Start Page | 73
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End Page | 92
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ISSN | 0475-0071
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NCID | AA10699856
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Content Type |
Departmental Bulletin Paper
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OAI-PMH Set |
岡山大学
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language |
English
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File Version | publisher
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NAID | |
Eprints Journal Name | mfe
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