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Ítem Ellipse-based principal component analysis for self-intersecting curve reconstruction from noisy point sets(SPRINGER, 2011-03-01) Ruiz, O.; Vanegas, C.; Cadavid, C.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAESurface reconstruction from cross cuts usually requires curve reconstruction from planar noisy point samples. The output curves must form a possibly disconnected 1-manifold for the surface reconstruction to proceed. This article describes an implemented algorithm for the reconstruction of planar curves (1-manifolds) out of noisy point samples of a self-intersecting or nearly self-intersecting planar curve C. C:[a,b]R?R 2 is self-intersecting if C(u)=C(v), u v, u,v (a,b) (C(u) is the self-intersection point). We consider only transversal self-intersections, i.e. those for which the tangents of the intersecting branches at the intersection point do not coincide (C (u)=C(v)). In the presence of noise, curves which self-intersect cannot be distinguished from curves which nearly self-intersect. Existing algorithms for curve reconstruction out of either noisy point samples or pixel data, do not produce a (possibly disconnected) Piecewise Linear 1-manifold approaching the whole point sample. The algorithm implemented in this work uses Principal Component Analysis (PCA) with elliptic support regions near the self-intersections. The algorithm was successful in recovering contours out of noisy slice samples of a surface, for the Hand, Pelvis and Skull data sets. As a test for the correctness of the obtained curves in the slice levels, they were input into an algorithm of surface reconstruction, leading to a reconstructed surface which reproduces the topological and geometrical properties of the original object. The algorithm robustly reacts not only to statistical non-correlation at the self-intersections (non-manifold neighborhoods) but also to occasional high noise at the non-self-intersecting (1-manifold) neighborhoods. © 2010 Springer-Verlag.Ítem Ellipse-based principal component analysis for self-intersecting curve reconstruction from noisy point sets(SPRINGER, 2011-03-01) Ruiz, O.; Vanegas, C.; Cadavid, C.; Ruiz, O.; Vanegas, C.; Cadavid, C.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y AplicacionesSurface reconstruction from cross cuts usually requires curve reconstruction from planar noisy point samples. The output curves must form a possibly disconnected 1-manifold for the surface reconstruction to proceed. This article describes an implemented algorithm for the reconstruction of planar curves (1-manifolds) out of noisy point samples of a self-intersecting or nearly self-intersecting planar curve C. C:[a,b]R?R 2 is self-intersecting if C(u)=C(v), u v, u,v (a,b) (C(u) is the self-intersection point). We consider only transversal self-intersections, i.e. those for which the tangents of the intersecting branches at the intersection point do not coincide (C (u)=C(v)). In the presence of noise, curves which self-intersect cannot be distinguished from curves which nearly self-intersect. Existing algorithms for curve reconstruction out of either noisy point samples or pixel data, do not produce a (possibly disconnected) Piecewise Linear 1-manifold approaching the whole point sample. The algorithm implemented in this work uses Principal Component Analysis (PCA) with elliptic support regions near the self-intersections. The algorithm was successful in recovering contours out of noisy slice samples of a surface, for the Hand, Pelvis and Skull data sets. As a test for the correctness of the obtained curves in the slice levels, they were input into an algorithm of surface reconstruction, leading to a reconstructed surface which reproduces the topological and geometrical properties of the original object. The algorithm robustly reacts not only to statistical non-correlation at the self-intersections (non-manifold neighborhoods) but also to occasional high noise at the non-self-intersecting (1-manifold) neighborhoods. © 2010 Springer-Verlag.Ítem Face reconstruction with structured light(INSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATION, 2011-01-01) Congote, J.; Barandiaran, I.; Barandiaran, J.; Nieto, M.; Ruiz, O.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEThis article presents a methodology for reconstruction of 3D faces which is based on stereoscopic images of the scene using active and passive surface reconstruction. A sequence of Gray patterns is generated, which are projected onto the scene and their projection recorded by a pair of stereo cameras. The images are rectified to make coincident their epipolar planes and so to generate a stereo map of the scene. An algorithm for stereo matching is applied, whose result is a bijective mapping between subsets of the pixels of the images. A particular connected subset of the images (e.g. the face) is selected by a segmentation algorithm. The stereo mapping is applied to such a subset and enables the triangulation of the two image readings therefore rendering the (x,y,z) points of the face, which in turn allow the reconstruction of the triangular mesh of the face. Since the surface might have holes, bilateral filters are applied to have the holes filled. The algorithms are tested in real conditions and we evaluate their performance with virtual datasets. Our results show a good reconstruction of the faces and an improvement of the results of passive systems.Ítem Low altitude wind simulation over mount saint helens using NASA SRTM digital terrain model(2007-01-01) Garcia, M.J.; Boulanger, P.; Garcia, M.J.; Boulanger, P.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Mecánica AplicadaOn February 11, 2000, the Shuttle Radar Topography Mission (SRTM) was launched into space as part of one of the pay load of the Shuttle Endeavor. Using a new radar sweeping technique most of the Earth's surfaces was digitized in 3D in approximately 10 days. SRTM acquired enough data during its mission to obtain a near-global high-resolution database of the Earth's topography. This paper describe how this revolutionary data set can be used to simulate anywhere around the Earth low altitude wind conditions for various atmospheric conditions. More specifically, we will describe the various processing steps necessary to convert this high-resolution terrain model provided by the SRTM database into a Computational Fluid Dynamic (CFD) volumetric mesh that is compatible with an open source CFD solver called OpenFOAM running in parallel on large West-Grid supercomputers. This work is the result of a new virtual wind-tunnel under development at the University of Alberta. In the paper, we present wind flow over the MountSaint Helens in the United States for a simple wind flow boundary condition. © 2006 IEEE.Ítem Statistical tuning of adaptive-weight depth map algorithm(SPRINGER, 2011-01-01) Hoyos, Alejandro; Congote, John; Barandiaran, Inigo; Acosta, Diego; Ruiz, Oscar; Universidad EAFIT. Departamento de Ingeniería de Procesos; Desarrollo y Diseño de ProcesosIn depth map generation, the settings of the algorithm parameters to yield an accurate disparity estimation are usually chosen empirically or based on unplanned experiments. A systematic statistical approach including classical and exploratory data analyses on over 14000 images to measure the relative influence of the parameters allows their tuning based on the number of bad-pixels. Our approach is systematic in the sense that the heuristics used for parameter tuning are supported by formal statistical methods. The implemented methodology improves the performance of dense depth map algorithms. As a result of the statistical based tuning, the algorithm improves from 16.78% to 14.48% bad-pixels rising 7 spots as per the Middlebury Stereo Evaluation Ranking Table. The performance is measured based on the distance of the algorithm results vs. the Ground Truth by Middlebury. Future work aims to achieve the tuning by using significantly smaller data sets on fractional factorial and surface-response designs of experiments. © 2011 Springer-Verlag.