Direct least-squares fitting of algebraic surfaces
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
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
Rationalising the Renormalisation Method of Kanatani
Journal of Mathematical Imaging and Vision
Statistical Optimization for Geometric Computation: Theory and Practice
Statistical Optimization for Geometric Computation: Theory and Practice
Image histogram thresholding based on multiobjective optimization
Signal Processing
Non-supervised image segmentation based on multiobjective optimization
Pattern Recognition Letters
A compact and accurate Gaussian variate generator
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
A flexible layered architecture for accurate digital baseband algorithm development and verification
Proceedings of the Conference on Design, Automation and Test in Europe
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We study a popular algorithm for fitting polynomial curves to scattered data based on the least squares with gradient weights. We show that sometimes this algorithm admits a substantial reduction of complexity, and, furthermore, find precise conditions under which this is possible. It turns out that this is, indeed, possible when one fits circles but not ellipses or hyperbolas.