Parameter Estimates for a Pencil of Lines: Bounds and Estimators

Authors:
Gavriel Speyer;Michael Werman
Affiliations:
-;-
Venue:
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Year:
2002

Citing 5
Cited 2

Fundamentals of statistical signal processing: estimation theory

Fundamentals of statistical signal processing: estimation theory
Computer Vision: A Modern Approach

Computer Vision: A Modern Approach
Optimal Motion and Structure Estimation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Optimization for Geometric Computation: Theory and Practice

Statistical Optimization for Geometric Computation: Theory and Practice
On the second-order statistics of the eigenvectors of samplecovariance matrices

IEEE Transactions on Signal Processing

All points considered: a maximum likelihood method for motion recovery

Proceedings of the 11th international conference on Theoretical foundations of computer vision
Algebraic error analysis of collinear feature points for camera parameter estimation

Computer Vision and Image Understanding

Quantified Score

Hi-index	0.00

Visualization

Abstract

Estimating the parameters of a pencil of lines is addressed. A statistical model for the measurements is developed, from which the Cramer Rao lower bound is determined. An estimator is derived, and its performance is simulated and compared to the bound. The estimator is shown to be asymptotically efficient, and superior to the classical least squares algorithm.