Abstract
We derive here a theoretical accuracy limit of the geometric estimation problem in the general mathematical framework described in Chaps. 14 and 15. It is given in the form of a bound, called the KCR (Kanatani-Cramer-Rao) lower bound, on the covariance matrix of the solution \(\varvec{\theta }\). The resulting form indicates that all iterative algebraic and geometric methods achieve this bound up to higher-order terms in \(\sigma \), meaning that these are all optimal with respect to covariance. As in Chaps. 14 and 15, we treat \(\varvec{\theta }\) and \(\varvec{\xi }_{\alpha }\) as nD vectors for generality.
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References
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Kanatani, K., Sugaya, Y., Kanazawa, Y. (2016). Theoretical Accuracy Limit. In: Guide to 3D Vision Computation. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-48493-8_16
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DOI: https://doi.org/10.1007/978-3-319-48493-8_16
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