Robust regression and outlier detection
Robust regression and outlier detection
A new curve detection method: randomized Hough transform (RHT)
Pattern Recognition Letters
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
Robust Adaptive Segmentation of Range Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
MLESAC: a new robust estimator with application to estimating image geometry
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Optimization for Geometric Computation: Theory and Practice
Statistical Optimization for Geometric Computation: Theory and Practice
Robust Estimation for Range Image Segmentation and Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Preemptive RANSAC for Live Structure and Motion Estimation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Robust Regression with Projection Based M-estimators
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
MDPE: A Very Robust Estimator for Model Fitting and Range Image Segmentation
International Journal of Computer Vision
Robust Adaptive-Scale Parametric Model Estimation for Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching with PROSAC " Progressive Sample Consensus
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Two-View Geometry Estimation Unaffected by a Dominant Plane
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
The Modified pbM-Estimator Method and a Runtime Analysis Technique for the RANSAC Family
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Heteroscedastic Projection Based M-Estimators
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
RANSAC for (Quasi-)Degenerate data (QDEGSAC)
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Beyond RANSAC: User Independent Robust Regression
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling the World from Internet Photo Collections
International Journal of Computer Vision
Robust Scale Estimation from Ensemble Inlier Sets for Random Sample Consensus Methods
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Automatic Estimation of the Inlier Threshold in Robust Multiple Structures Fitting
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
A Generalized Kernel Consensus-Based Robust Estimator
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneously Fitting and Segmenting Multiple-Structure Data with Outliers
IEEE Transactions on Pattern Analysis and Machine Intelligence
RECON: Scale-adaptive robust estimation via Residual Consensus
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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This paper addresses the general problem of robust parametric model estimation from data that has both an unknown (and possibly majority) fraction of outliers as well as an unknown scale of measurement noise. We focus on computer vision applications from image correspondences, such as camera resectioning, estimation of the fundamental matrix or relative pose for 3D reconstruction, and estimation of 2D homographies for image registration and motion segmentation, although there are many other applications. In practice, these methods typically rely on a predefined inlier thresholds because automatic scale detection is usually too unreliable or too slow. We propose a new method for robust estimation with automatic scale detection that is faster, more precise and more robust than previous alternatives, and show that it can be practically applied to these problems.