IEEE Transactions on Pattern Analysis and Machine Intelligence
Cramer-Rao lower bounds for curve fitting
Graphical Models and Image Processing
Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint
International Journal of Computer Vision - Special issue on a special section on visual surveillance
On the Fitting of Surfaces to Data with Covariances
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rationalising the Renormalisation Method of Kanatani
Journal of Mathematical Imaging and Vision
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Stochastic Complexity in Statistical Inquiry Theory
Stochastic Complexity in Statistical Inquiry Theory
From FNS to HEIV: A Link between Two Vision Parameter Estimation Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Uncertainty Modeling and Model Selection for Geometric Inference
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Optimization for Geometric Computation: Theory and Practice
Statistical Optimization for Geometric Computation: Theory and Practice
FNS, CFNS and HEIV: A Unifying Approach
Journal of Mathematical Imaging and Vision
Further Improving Geometric Fitting
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
How to Put Probabilities on Homographies
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Riemannian Framework for Tensor Computing
International Journal of Computer Vision
Ellipse Fitting with Hyperaccuracy
IEICE - Transactions on Information and Systems
High Accuracy Fundamental Matrix Computation and Its Performance Evaluation
IEICE - Transactions on Information and Systems
Performance evaluation of iterative geometric fitting algorithms
Computational Statistics & Data Analysis
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Compact Fundamental Matrix Computation
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Error Analysis in Homography Estimation by First Order Approximation Tools: A General Technique
Journal of Mathematical Imaging and Vision
Estimating homographies without normalization
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Unified Computation of Strict Maximum Likelihood for Geometric Fitting
Journal of Mathematical Imaging and Vision
Hyper least squares fitting of circles and ellipses
Computational Statistics & Data Analysis
GlobFit: consistently fitting primitives by discovering global relations
ACM SIGGRAPH 2011 papers
Computational Statistics & Data Analysis
Renormalization returns: hyper-renormalization and its applications
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Optimization techniques for geometric estimation: beyond minimization
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Image and Vision Computing
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A rigorous accuracy analysis is given to various techniques for estimating parameters of geometric models from noisy data. First, it is pointed out that parameter estimation for vision applications is very different in nature from traditional statistical analysis and hence a different mathematical framework is necessary. After a general framework is formulated, typical numerical techniques are selected, and their accuracy is evaluated up to high order terms. As a byproduct, our analysis leads to a "hyperaccurate" method that outperforms existing methods.