Optimal Computation of 3-D Similarity from Space Data with Inhomogeneous Noise Distributions
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抄録
We optimally estimate the similarity (rotation, translation, and scale change) between two sets of 3-D data in the presence of inhomogeneous and anisotropic noise. Adopting the Lie algebra representation of the 3-D rotational change, we derive the Levenberg-Marquardt procedure for simultaneously optimizing the rotation, the translation, and the scale change. We test the performance of our method using simulated stereo data and real GPS geodetic sensing data. We conclude that the conventional method assuming homogeneous and isotropic noise is insufficient and that our simultaneous optimization scheme can produce an accurate solution.
収録刊行物
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- Memoirs of the Faculty of Engineering, Okayama University
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Memoirs of the Faculty of Engineering, Okayama University 46 1-9, 2012-01
Faculty of Engineering, Okayama University
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詳細情報 詳細情報について
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- CRID
- 1390572174776246400
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- NII論文ID
- 80022451620
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- NII書誌ID
- AA12014085
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- ISSN
- 13496115
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- DOI
- 10.18926/48125
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- IRDB
- CiNii Articles
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