Search Results

Now showing 1 - 2 of 2
  • Item
    Robust Method for Estimating Normals on Point Clouds Using Adaptive Neighborhood Size
    (The Eurographics Association, 2021) Leal, E.A.; Leal, N.E.; Silva, F. and Gutierrez, D. and Rodríguez, J. and Figueiredo, M.
    Normal estimation on sampled curves or surfaces is a basic step of many algorithms in computer graphics, computer vision, and especially in recognition and reconstruction of three dimensional objects. This paper presents a simple and intuitive method for estimating normals on point based surfaces. The method is based on Robust Principal Component Analysis (RPCA) therefore is capable to deal with noisy data and outliers. In order to estimate an accurate normal on a point, our method takes a neighborhood of variable size around the point. The neighborhood size depends on local properties of the sampled surface. It is shown that the estimation of the tangent plane on a point is more accurate using a neighborhood of variable size than using a fixed one.
  • Item
    3D Visualization of Sparse Geophysical Data Representing Uncertainty
    (The Eurographics Association, 2021) Gonçalves, Vítor; Dias, Paulo; Almeida, Fernando; Madeira, Joaquim; Santos, Beatriz Sousa; Silva, F. and Gutierrez, D. and Rodríguez, J. and Figueiredo, M.
    Geophysical data are sparse and by nature difficult to analyze. Usually domain experts use "mental models" to infer missing data according to the surrounding data and their own knowledge. The main goal of this work is to explore the best way to represent uncertainty in geophysical data. Given the sparse nature of the represented data, it is important to provide a 3D volumetric representation of the whole subsoil, based on a geostatistical process. We use kriging interpolation to generate a structured grid from the original sparse data. However, the analysis of such an interpolated representation must be careful, since the uncertainty varies significantly according to the distance to real measurements. We use different representations to emphasize data uncertainty during the analysis stage. The different visualization techniques implemented in our prototype, as well as methods used to simultaneously visualize resistivity and uncertainty information, are presented.