Based on sampling likelihood and feature intensity, in this paper, a feature-preserving denoising algorithm for point-sampled surfaces is proposed. In terms of moving least squares surface, the sampling likelihood for each point on point-sampled surfaces is computed, which measures the probability that a 3D point is located on the sampled surface. Based on the normal tensor voting, the feature ...

In this paper, we analyze the weight functions used in implicit moving least squares (IMLS) methods to construct implicit surfaces that interpolate or approximate polygon soup. We found that one method that presented an analytic solution to the integrated moving least squares method has issues with degeneracies because they changed the weight functions to decrease too slowly. We derive bounds f...

In this paper we report some recent advances regarding applications using the method of finite spheres; a truly meshfree numerical technique developed for the solution of boundary value problems on geometrically complex domains. First, we present the development of a preprocessor for the generation of nodal points on twodimensional computational domains. Then, the development of a specialized v...

By combining the well known moving least squares approximation method and the theory of approximate approximations due to Maz’ya and Schmidt we are able to present an approximate moving least squares method which inherits the simplicity of Shepard’s method along with the accuracy of higher-order moving least squares approximations. In this paper we focus our interest on practical implementation...

While digital panoramic photography taken along travelling routes is very popular, digital panoramic strip maps are virtually nonexistent. In this article, we explore the characteristics of panoramic strip maps and provide an interactive method for their digital creation, focusing on the challenge of straightening curved routes. The resulting software Terrain Bender implements a geometric defor...

Meshless methods have been extensively popularized in literature in recent years, due to their flexibility in solving boundary value problems. The meshless local Petrov-Galerkin(MLPG) method for solving the bending problem of the thin plate is presented and discussed in the present paper. The method uses the moving least-squares approximation to interpolate the solution variables, and employs a...

We present a new method for point cloud denoising. We introduce a robust smoothing operator Q(r) = r + t∗n∗, inspired in moving least squares and M-estimators robust statistics theory. Our algorithm can be seen as a generalization and improvement of the Fleishman et al algorithm for mesh denoising.

This paper addresses the problem of identifying echelon canonical forms for a vector autoregressive moving average model with exogenous variables using finite algorithms. For given values of the Kronecker indices a method for estimating the structural parameters of a model using ordinary least squares calculations is presented. These procedures give rise, rather naturally, to a technique for th...

Based on sampling likelihood and feature intensity, in this paper, a feature-preserving denoising algorithm for point-sampled surfaces is proposed. In terms of moving least squares surface, the sampling likelihood for each point on point-sampled surfaces is computed, which measures the probability that a 3D point is located on the sampled surface. Based on the normal tensor voting, the feature ...