This article describes an approach based on hierarchical radial basis functions to reconstruction and modification of motion / image data, which are formulated as problems of scattered data interpolation. Assuming little about the data and choosing highly scalable / well adjustable basis functions, the approach can handle both the reconstruction and the manipulation in a unified and widely appl...

A lemma of Micchelli’s, concerning radial polynomials and weighted sums of point evaluations, is shown to hold for arbitrary linear functionals, as is Schaback’s more recent extension of this lemma and Schaback’s result concerning interpolation by radial polynomials. Schaback’s interpolant is explored. In his most-cited paper, [M], Micchelli supplies the following interesting auxiliary lemma (h...

In this paper we propose a Rescaled Localized Radial Basis Functions (RL-RBF) interpolation method, based on the use of compactly supported radial basis functions. Starting from classic RBF interpolation technique, we introduce a rescaling that recovers the partition of unity combined with a new algorithm to select the support of the basis. The proposed rescaling generates a set of basis functi...

In this paper, we propose a new numerical method for solution of Urysohn two dimensional mixed Volterra-Fredholm integral equations of the second kind on a non-rectangular domain. The method approximates the solution by the discrete collocation method based on inverse multiquadric radial basis functions (RBFs) constructed on a set of disordered data. The method is a meshless method, because it ...

In this paper, an extension of our previous research focused on haptic rendering based on interpolation from precomputed data is presented. The technique employs the radial-basis function (RBF) interpolation to achieve the accuracy of the force response approximation, however, it assumes that the data used by the interpolation method are generated on-the-fly during the haptic interaction. The i...

We discuss the problem of constrained approximation and interpolation of scattered data by using compactly supported radial basis functions, subjected to the constraint of preserving positivity. The approaches are presented to compute positive approximation and interpolation by solving the two corresponding optimization problems. Numerical experiments are provided to illustrate that the propose...

A multilevel kernel-based interpolation method, suitable for moderately high-dimensional function interpolation problems, is proposed. The method, termed multilevel sparse kernelbased interpolation (MLSKI, for short), uses both level-wise and direction-wise multilevel decomposition of structured (or mildly unstructured) interpolation data sites in conjunction with the application of kernel-base...