鲁棒回归之Least Median of Squares(LMedS) 简介 这里我们来看一个比较少见的鲁棒回归中的方法:最小中值二乘法(Least Median of Squares, LMedS),其对应的优化问题为: 为残差,为优化变量(1)argminβ S(β)=median(ri2),ri为残差,β为优化变量 它和最小二乘法不同,最小二乘法本质上就是优化均值,LMedS...
鲁棒回归之Least Median of Squares(LMedS) 这里我们来看另一个鲁棒回归中的方法:截断最小二乘法(Least Trimmed Squares, LTS),顾名思义,这个方法会把一部分残差剔除,它可以显式地剔除野值点的影响。 鲁棒回归中抛锚点概念 抛锚点 ϵ (Breakdown Point)是指样本中最高脏数据的比例,在该比例下,估计量(Estimato...
The robust least-median-of-squares (LMedS) estimator, which can recover a model representing only half the data points, was recently introduced in computer vision. Image data, however, is usually also corrupted by a zero-mean random process (noise) accounting for the measurement uncertainties. ...
Robust estimators, such as least median of squared (LMedS) residuals, M-estimators, the least trimmed squares (LTS) etc., have been employed to estimate op... H Wang,D Suter - IEEE International Conference on Computer Vision 被引量: 40发表: 2003年 Applications and algorithms for least trimm...
The algorithm uses the least median of squares (LMedS) estimator recently introduced in the statistics literature. We show that the estimator may yield incorrect results when applied to images, and propose a two-stage procedure for the local description of the image structure and of the corrupting...
The backbone of the proposed technique is the conventional Least Median of Squares (LMedS) technique. It is well known that the LMedS is one of the most robust regressors for highly contaminated data and unstable models. Unfortunately, its computational complexity renders it useless for practical ...
The backbone of the proposed technique is the conventional Least Median of Squares (LMedS) technique. It is well known that the LMedS is one of the most robust regressors for highly contaminated data and unstable models. Unfortunately, its computational complexity renders it useless for practical ...
The backbone of the proposed technique is the conventional Least Median of Squares (LMedS) technique. It is well known that the LMedS is one of the most robust regressors for highly contaminated data and unstable models. Unfortunately, its computational complexity renders it useless for practical ...
least-median-of-squares robust regressionmotion discontinuity detectionoptical flow estimationAn optical flow estimation technique is presented which is based on the least-median-of-squares (LMedS) robust regression algorithm enabling more accurate flow estimates to be computed in the vicin......
Of these, those that are based on the LMedS (Least Median of Squares) appear to be the most robust. The goal of this paper is to carry out an error analysis of two different LMedS-based approaches, one based on the standard LMedS regression and the other using a modification thereof as...