REPO

Memoirs of the Faculty of Engineering, Okayama University 45巻
2011-01 発行

Optimal Computation of 3-D Rotation under Inhomogeneous Anisotropic Noise

Kanatani, Kenichi Department of Computer Science, Okayama University Kaken ID publons researchmap
Niitsuma, Hirotaka Department of Computer Science, Okayama University ORCID Kaken ID publons researchmap
Publication Date
2011-01
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.
ISSN
1349-6115
NCID
AA12014085
NAID