SIAM Journal on Matrix Analysis and Applications
Recursive estimation of motion parameters
Computer Vision and Image Understanding
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint
International Journal of Computer Vision - Special issue on a special section on visual surveillance
The Role of Total Least Squares in Motion Analysis
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
When are Simple LS Estimators Enough? An Empirical Study of LS, TLS, and GTLS
International Journal of Computer Vision
On the Consistency of the Normalized Eight-Point Algorithm
Journal of Mathematical Imaging and Vision
Editorial: Total Least Squares and Errors-in-variables Modeling
Computational Statistics & Data Analysis
Editorial: 2nd Special issue on matrix computations and statistics
Computational Statistics & Data Analysis
An extended system method for consistent fundamental matrix estimation
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Sampling Minimal Subsets with Large Spans for Robust Estimation
International Journal of Computer Vision
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Consistent estimators of the rank-deficient fundamental matrix yielding information on the relative orientation of two images in two-view motion analysis are derived. The estimators are derived by minimizing a corrected contrast function in a quadratic measurement error model. In addition, a consistent estimator for the measurement error variance is obtained. Simulation results show the improved accuracy of the newly proposed estimator compared to the ordinary total least-squares estimator.