Cramer-Rao Bounds for Nonparametric Surface Reconstruction from Range Data
Abstract
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 important tool in 3D reconstruction, and are particularly useful for representing complex scenes with arbitrary shapes and topologies. This paper presents 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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 18, 2003
- Accession Number
- ADA478716
Entities
People
- Ross Whitaker
- Tolga Tasdizen
Organizations
- University of Utah