REPO

Memoirs of the Faculty of Engineering, Okayama University volume46
2012-01 発行

Optimal Computation of 3-D Similarity from Space Data with Inhomogeneous Noise Distributions

Publication Date
2012-01
Abstract
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.
ISSN
1349-6115
NCID
AA12014085
NAID