Measurement error models
Elements of statistical computing
Elements of statistical computing
Bootstrap Techniques for Error Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fitting ellipses and predicting confidence envelopes using a bias corrected Kalman filter
Image and Vision Computing - Special issue: 5th Alvey vision meeting
Accurate parameter estimation of quadratic curves from grey-level images
CVGIP: Image Understanding
Ellipse detection and matching with uncertainty
Image and Vision Computing - Special issue: BMVC 1991
Geometric computation for machine vision
Geometric computation for machine vision
A note on the least squares fitting of ellipses
Pattern Recognition Letters
Unbiased least square fitting of circular arcs
CVGIP: Graphical Models and Image Processing
Fitting a Second Degree Curve in the Presence of Error
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer and Robot Vision
Statistical Models in S
Statistical Bias of Conic Fitting and Renormalization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Quantitative evaluation of performance through bootstrapping: edge detection
ISCV '95 Proceedings of the International Symposium on Computer Vision
A Method to Detect and Characterize Ellipses Using the Hough Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint
International Journal of Computer Vision - Special issue on a special section on visual surveillance
A Simple Method of Radial Distortion Correction with Centre of Distortion Estimation
Journal of Mathematical Imaging and Vision
Precise ellipse estimation without contour point extraction
Machine Vision and Applications
Bootstrap resampling for image registration uncertainty estimation without ground truth
IEEE Transactions on Image Processing
Ellipse fitting with hyperaccuracy
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Bootstrap-based normal reconstruction
Proceedings of the 7th international conference on Curves and Surfaces
Edge curvature and convexity based ellipse detection method
Pattern Recognition
| Hi-index | 0.15 |
A general method for eliminating the bias of nonlinear estimators using bootstrap is presented. Instead of the traditional mean bias we consider the definition of bias based on the median. The method is applied to the problem of fitting ellipse segments to noisy data. No assumption beyond being independent identically distributed (i.i.d.) is made about the error distribution and experiments with both synthetic and real data prove the effectiveness of the technique.