Automatic Estimation of the Inlier Threshold in Robust Multiple Structures Fitting
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Efficient Random Sampling for Nonrigid Feature Matching
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Adaptive Sample Consensus for Efficient Random Optimization
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Non-rigid metric reconstruction from perspective cameras
Image and Vision Computing
Two-stage outlier elimination for robust curve and surface fitting
EURASIP Journal on Advances in Signal Processing - Special issue on robust processing of nonstationary signals
Efficient and robust model fitting with unknown noise scale
Image and Vision Computing
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This paper proposes a RANSAC modification that performs automatic estimation of the scale of inlier noise. The scale estimation takes advantage of accumulated inlier sets from all proposed models. It is shown that the proposed method gives robust results in case of high outlier ratio data, in spite that no user specified threshold is needed. The method also improves sampling efficiency, without requiring any auxiliary information other than the data to be modeled.