ID | 44496 |
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Sort Key | 3
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フルテキストURL | |
著者 |
Rangrajan, Prasanna
Department of Electrical Engineering, Southern Methodist University
Sugaya, Yasuyuki
Department of Computer Science and Engineering, Toyohashi University of Technology
Niitsuma, Hirotaka
Department of Computer Science, Okayama University
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抄録 | We present a new least squares (LS) estimator, called “HyperLS”, specifically designed for parameter estimation in computer vision applications. It minimizes the algebraic distance under a special scale normalization, which is derived by rigorous error analysis in such a way that statistical bias is removed up to second order noise terms. Numerical experiments suggest that our HyperLS is far superior to the standard LS and comparable in accuracy to maximum likelihood (ML), which is known to produce highly accurate results in image applications but may fail to converge if poorly initialized. Our HyperLS is a perfect candidate for ML initialization. In addition, we discuss how
image-based inference problems have different characteristics form conventional statistical applications, with a view to serving as a bridge between mathematicians and computer engineers.
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出版物タイトル |
Memoirs of the Faculty of Engineering, Okayama University
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発行日 | 2011-01
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巻 | 45巻
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出版者 | Faculty of Engineering, Okayama University
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開始ページ | 15
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終了ページ | 26
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ISSN | 1349-6115
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NCID | AA12014085
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資料タイプ |
紀要論文
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OAI-PMH Set |
岡山大学
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言語 |
英語
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著作権者 | Copyright © by the authors
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論文のバージョン | publisher
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査読 |
無し
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NAID | |
Eprints Journal Name | mfe
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