### Abstract

We present a new method for optimally computing the 3-D rotation from two sets of 3-D data in the presence of inhomogeneous and anisotropic noise. Following Ohta and Kanatani, we adopt the quaternion representation of 3-D rotation and compute an exact maximum likelihood solution using the FNS of Chojnacki et al. Then, the uncertainty of 3-D reconstruction by stereo vision is analyzed, and the 3-D rotation is optimally computed. We show that the renormalization of Ohta and Kanatani indeed computes almost an optimal solution and that the proposed method can compute an even better solution.

Original language | English |
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Title of host publication | Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011 |

Pages | 112-115 |

Number of pages | 4 |

Publication status | Published - 2011 |

Event | 12th IAPR Conference on Machine Vision Applications, MVA 2011 - Nara, Japan Duration: Jun 13 2011 → Jun 15 2011 |

### Other

Other | 12th IAPR Conference on Machine Vision Applications, MVA 2011 |
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Country | Japan |

City | Nara |

Period | 6/13/11 → 6/15/11 |

### Fingerprint

### ASJC Scopus subject areas

- Computer Vision and Pattern Recognition

### Cite this

*Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011*(pp. 112-115)

**Optimal computation of 3-D rotation under inhomogeneous anisotropic noise.** / Niitsuma, Hirotaka; Kanatani, Kenichi.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011.*pp. 112-115, 12th IAPR Conference on Machine Vision Applications, MVA 2011, Nara, Japan, 6/13/11.

}

TY - GEN

T1 - Optimal computation of 3-D rotation under inhomogeneous anisotropic noise

AU - Niitsuma, Hirotaka

AU - Kanatani, Kenichi

PY - 2011

Y1 - 2011

N2 - We present a new method for optimally computing the 3-D rotation from two sets of 3-D data in the presence of inhomogeneous and anisotropic noise. Following Ohta and Kanatani, we adopt the quaternion representation of 3-D rotation and compute an exact maximum likelihood solution using the FNS of Chojnacki et al. Then, the uncertainty of 3-D reconstruction by stereo vision is analyzed, and the 3-D rotation is optimally computed. We show that the renormalization of Ohta and Kanatani indeed computes almost an optimal solution and that the proposed method can compute an even better solution.

AB - We present a new method for optimally computing the 3-D rotation from two sets of 3-D data in the presence of inhomogeneous and anisotropic noise. Following Ohta and Kanatani, we adopt the quaternion representation of 3-D rotation and compute an exact maximum likelihood solution using the FNS of Chojnacki et al. Then, the uncertainty of 3-D reconstruction by stereo vision is analyzed, and the 3-D rotation is optimally computed. We show that the renormalization of Ohta and Kanatani indeed computes almost an optimal solution and that the proposed method can compute an even better solution.

UR - http://www.scopus.com/inward/record.url?scp=84864126822&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84864126822&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84864126822

SN - 9784901122115

SP - 112

EP - 115

BT - Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

ER -