ID 44498
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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.
Publication Title
Memoirs of the Faculty of Engineering, Okayama University
Published Date
2011-01
Volume
volume45
Publisher
Faculty of Engineering, Okayama University
Start Page
36
End Page
45
ISSN
1349-6115
NCID
AA12014085
Content Type
Departmental Bulletin Paper
OAI-PMH Set
岡山大学
language
英語
Copyright Holders
Copyright © by the authors
File Version
publisher
NAID
Eprints Journal Name
mfe