ID | 44498 |
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Sort Key | 5
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Abstract | We present a new method for optimally computing the 3-D rotation from two sets of 3-D data.
Unlike 2-D data, the noise in 3-D data is inherently inhomogeneous and anisotropic, reflecting the characteristics of the 3-D sensing used. To cope with this, Ohta and Kanatani introduced a technique called “renormalization”. Following them, we represent a 3-D rotation in terms of a quaternion and compute an exact maximum likelihood solution using the FNS of Chojnacki et
al. As an example, we consider 3-D data obtained by stereo vision and optimally compute the 3-D rotation by analyzing the noise characteristics of stereo reconstruction. We show that the widely used method is not suitable for 3-D data. We confirm that the renormalization of Ohta and
Kanatani indeed computes almost an optimal solution and that, although the difference is small, the proposed method can compute an even better solution.
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Publication Title |
Memoirs of the Faculty of Engineering, Okayama University
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Published Date | 2011-01
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Volume | volume45
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Publisher | Faculty of Engineering, Okayama University
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Start Page | 36
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End Page | 45
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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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Copyright Holders | Copyright © by the authors
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File Version | publisher
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NAID | |
Eprints Journal Name | mfe
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