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» Robust Regression with Projection Based M-estimators
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ICCV
2003
IEEE
14 years 6 months ago
Robust Regression with Projection Based M-estimators
The robust regression techniques in the RANSAC family are popular today in computer vision, but their performance depends on a user supplied threshold. We eliminate this drawback ...
Haifeng Chen, Peter Meer
ICASSP
2010
IEEE
13 years 5 months ago
Robust regression using sparse learning for high dimensional parameter estimation problems
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
CVPR
2005
IEEE
14 years 7 months ago
The Modified pbM-Estimator Method and a Runtime Analysis Technique for the RANSAC Family
Robust regression techniques are used today in many computer vision algorithms. Chen and Meer recently presented a new robust regression technique named the projection based M-est...
Stas Rozenfeld, Ilan Shimshoni
ECCV
2002
Springer
14 years 6 months ago
Robust Computer Vision through Kernel Density Estimation
Abstract. Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently emplo...
Haifeng Chen, Peter Meer
MICCAI
2007
Springer
14 years 5 months ago
Effectiveness of the Finite Impulse Response Model in Content-Based fMRI Image Retrieval
The thresholded t-map produced by the General Linear Model (GLM) gives an effective summary of activation patterns in functional brain images and is widely used for feature selecti...
Bing Bai, Paul B. Kantor, Ali Shokoufandeh