- 出版者
- Faculty of Engineering, Okayama University
- 雑誌
- Memoirs of the Faculty of Engineering, Okayama University (ISSN:13496115)
- 巻号頁・発行日
- vol.45, pp.36-45, 2011-01
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 etal. 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 andKanatani indeed computes almost an optimal solution and that, although the difference is small, the proposed method can compute an even better solution.