Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
Journal of Computational and Applied Mathematics
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 Regression with Projection Based M-estimators
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Robust Adaptive-Scale Parametric Model Estimation for Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear Mean Shift for Clustering over Analytic Manifolds
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
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
Robust Multiple Structures Estimation with J-Linkage
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Nonparametric estimation of multiple structures with outliers
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Editor's Choice Article: Image-consistent patches from unstructured points with J-linkage
Image and Vision Computing
Efficient and robust model fitting with unknown noise scale
Image and Vision Computing
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This paper tackles the problem of estimating the inlier threshold in RANSAC-like approaches to multiple models fitting. An iterative approach finds the maximum of a score function which resembles the Silhouette index used in clustering validation. Although several methods have been proposed to solve this problem for the single model case, this is the first attempt to address multiple models. Experimental results demonstrate the performances of the algorithm.