Image warping plays an extremely important role in face matching and recognition and therefore has wide applications and great significance in computer vision, biomedical imaging and homeland security. One popular warping algorithm developed by Alex Rosen, known as AlexWarp has the drawback that it only allows one pair of landmarks being specified at one time. The consequence of this is that th...

Traditional forecast verification is conducted for a single point location. When faced with a grid of points, the usual approach has been to perform forecast verification point by point. Such a strategy is inadequate because it ignores the spatial structure of the field, is highly susceptible to the double penalty problem (especially for higher resolution forecasts), and it does not provide use...

Description of mapping methods using spherical splines, both to interpolate scalp potentials (SPs), and to approximate scalp current densities (SCDs). Compared to a previously published method using thin plate splines, the advantages are a very simple derivation of the SCD approximation, faster computing times, and greater accuracy in areas with few electrodes.

We give some empirical comparisons between two nonparametric regression methods based on regularization: the elastic or thin-plate splines, and plastic splines based on total variation penalties. 1. Nonparametric regression with elastic and plastic splines We seek f to fit the dependence of response points zi ∈ R on two-dimensional covariates (xi, yi) living in the domain Ω. To this end, we emp...

Elastic splines (including dynamic \snakes" and elastic contours), minimising an energy norm of the membrane and/or thin-plate types, have been used to model many surfaces in visual reconstruction and related biomedical applications. In this paper, we model the displacement of the material between successive cardiac images using vector splines. We deene a family of elastic splines. These spline...

A major task in data mining is to develop automatic techniques to process and to detect patterns in very large data sets. Multivariate regression techniques form the core of many data mining applications. A common assumption is that the multivariate data is well approximated by an additive model involving only first and second order interaction terms. In this case high-dimensional nonparametric...

Global change research has placed new demands on methods of spatial analysis. In particular, spherical methods for spatial interpolation are required when spatial analyses are performed over large areas of the Earth's surface. In this article, spherical spatial interpolation procedures are reviewed, compared, and evaluated. Three classesof spherical interpolants are evaluated in detail: distanc...

Amajor task in data mining is to develop automatic techniques to process and to detect patterns in very large data sets. An important data mining technique is multivariate regression, and an essential sub task is the estimation of interaction surfaces, i.e. the estimation of functions of two variables. Thin plate splines provide a very good method to determine an approximating surface. Obtainin...