Robust estimation of hydrogeologic model parameters

Robust estimation of hydrogeologic model parameters

Inverse modeling has become a standard technique for estimating hydrogeologic parameters. These parameters are usually inferred by minimizing the sum of the squared differences between the observed system state and the one calculated by a mathematical model. The robustness of the least squares criterion, however, has to be questioned because of the tendency of outliers in the measurements to st...

Robust Estimation of Tail Parameters

Robust estimation of shape parameters

We investigate the use of Robust Estimation in an application requiring the accurate location of the centres of circular objects in an image. A common approach used throughout computer vision for extracting shape information from a data set is to fit a feature model using the Least Squares method. The well known sensitivity of this method to outliers is traditionally accommodated by outlier rej...

Robust Scale Estimation from True Parameters of Model

In computer vision tasks, it frequently happens that gross noise and pseudo outliers occupy the absolute majority of the data. During the past several decades, a lot of robust estimators were developed to find parameters of a model from heavily contaminated data. However, correctly estimating the parameters of a model is not enough to differentiate inliers from outliers. Robust scale estimation...

Adaptive Robust Estimation of Model Parameters from Block Motion Vectors

In this paper, we propose a model parameter estimation algorithm from block motion vectors for extracting accurate motion information with the assumption that the undergoing motion can be characterized by an affine model. The motion may be caused either by a moving camera or a moving object. The proposed method first extracts motion vectors from a sequence of images by using sizevariable block ...