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Cramer-Rao bounds for nonparametric surface reconstruction from range data

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2 Author(s)
T. Tasdizen ; Sch. of Comput., Utah Univ., Salt Lake City, UT, USA ; R. Whitaker

The Cramer-Rao error bound provides a fundamental limit on the expected performance of a statistical estimator. The error bound depends on the general properties of the system, but not on the specific properties of the estimator or the solution. The Cramer-Rao error bound has been applied to scalar- and vector-valued estimators and recently to parametric shape estimators. However, nonparametric, low-level surface representations are an important tool in 3D reconstruction, and are particularly useful for representing complex scenes with arbitrary shapes and topologies. We present a generalization of the Cramer-Rao error bound to nonparametric shape estimators. Specifically, we derive the error bound for the full 3D reconstruction of scenes from multiple range images.

Published in:

3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings. Fourth International Conference on

Date of Conference:

6-10 Oct. 2003