Optimal Computation of 3-D Similarity from Space Data with Inhomogeneous Noise Distributions
Optimal Computation of 3-D Similarity from Space Data with Inhomogeneous Noise Distributions
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发表时间：
2011
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通讯作者：
K. Kanatani;Hirotaka Niitsuma
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作者：
K. Kanatani;Hirotaka Niitsuma
我们最佳估计的相似性（旋转，平移和尺度变化）在存在非均匀和各向异性噪声的两组3-D数据之间。采用三维旋转变化的李代数表示，我们推导出同时优化旋转、平移和尺度变化的Levenberg-Marquardt过程。我们使用模拟的立体数据和真实的GPS大地传感数据测试我们的方法的性能。我们的结论是，传统的方法假设均匀和各向同性噪声是不够的，我们的同时优化方案可以产生一个准确的解决方案。
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.