ID | 19955 |
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Sort Key | 3
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FullText URL | |
Author |
Sugaya Yasuyuki
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Abstract | A new numerical scheme is presented for computing strict maximum likelihood (ML) of geometric
fitting problems having an implicit constraint. Our approach is orthogonal projection of observations
onto a parameterized surface defined by the constraint. Assuming a linearly separable nonlinear constraint, we show that a theoretically global solution can be obtained by iterative Sampson error minimization. Our approach is illustrated by ellipse fitting and fundamental matrix computation. Our method also encompasses optimal correction, computing, e.g., perpendiculars to an ellipse and triangulating stereo images. A detailed discussion is given to technical and practical issues about our approach.
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Publication Title |
Memoirs of the Faculty of Engineering, Okayama University
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Published Date | 2010-01
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Volume | volume44
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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 | 13
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End Page | 23
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ISSN | 1349-6115
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NCID | AA12014085
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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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