LiDAR point cloud streams are usually sparse in time dimension, which is limited by hardware performance. Generally, the frame rates of mechanical sensors 10 to 20 Hz, much lower than other commonly used like cameras. To overcome temporal limitations sensors, a novel task named Point Cloud Frame Interpolation studied this paper. Given two consecutive frames, aims generate intermediate frame(s) ...

PSD allows you to move the creature to any pose and resculpt the skin surface in that pose. The sculpted alteration is smoothly (rather than linearly) interpolated as the creature moves to and away from that particular pose. Because the edits can occur at any pose, the underlying interpolation problem is one of scattered interpolation, as opposed to interpolation schemes such as splines that as...

We propose a novel approach to 3D image registration of intracellular volumes. The approach extends a standard image registration framework to the curved cell geometry. An intracellular volume is mapped onto another intracellular domain by using two pairs of point set surfaces approximating their nuclear and plasma membranes. The mapping function consists of the affine transformation, tetrahedr...

A simulation of a cantilever beam was carried out with the aim of comparing the performance of two mesh-free methods: element-free Galerkin and radial point interpolation methods. In this implementation, we use two different methods to set boundary conditions. The results were compared with the analytical solution of the cantilever problem using Timoshenko formulation [Tim70]. In the paper, we ...

A non-compactly supported cubic radial basis function implementation of the MLPG method for beam problems is presented. The evaluation of the derivatives of the shape functions obtained from the radial basis function interpolation is much simpler than the evaluation of the moving least squares shape function derivatives. The radial basis MLPG yields results as accurate or better than those obta...

Interpolation radial basis function (RBF) networks have been widely used in various applications. The output layer weights are usually determined by minimizing the sum-of-squares error or by directly solving interpolation equations. When the number of interpolation nodes is large, these methods are time consuming, difficult to control the balance between the convergence rate and the generality,...

Interpolation or approximation of scattered data is very often task in engineering problems. The Radial Basis Functions (RBF) interpolation is convenient for scattered (un-ordered) data sets in k-dimensional space, in general. This approach is convenient especially for a higher dimension k > 2 as the conversion to an ordered data set, e.g. using tessellation, is computationally very expensive. ...

Promising numerical results using once and twice integrated radial basis functions have been recently presented. In this work we investigate the integrated radial basis function (IRBF) concept in greater detail, connect to the existing RBF theory, and make conjectures about the properties of IRBF approximation methods. The IRBF methods are used to solve PDEs. c © 2006 Elsevier Science Ltd. All ...

This contribution presents a new analysis of properties of the interpolation using Radial Bases Functions (RBF) related to large data sets interpolation. The RBF application is convenient method for scattered d-dimensional interpolation. The RBF methods lead to a solution of linear system of equations and computational complexity of solution is nearly independent of a dimensionality. However, t...