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Examinando Artículos por Autor "Acosta, Diego"
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Ítem Fitting of Analytic Surfaces to Noisy Point Clouds(Scientific Research Publishing, 2013-04) Ruíz, Óscar; Arroyave, Santiago; Acosta, Diego; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEFitting -continuous or superior surfaces to a set of points sampled on a 2-manifold is central to reverse engi- neering, computer aided geometric modeling, entertaining, modeling of art heritage, etc -- This article addresses the fit- ting of analytic (ellipsoid, cones, cylinders) surfaces in general position in -- Currently, the state of the art presents limitations in 1) automatically finding an initial guess for the analytic surface F sought, and 2) economically estimat- ing the geometric distance between a point of and the analytic surface SF -- These issues are central in estimating an analytic surface which minimizes its accumulated distances to the point set -- In response to this situation, this article presents and tests novel user-independent strategies for addressing aspects 1) and 2) above, for cylinders, cones and ellipsoids -- A conjecture for the calculation of the distance point-ellipsoid is also proposed -- Our strategies produce good initial guesses for F and fast fitting error estimation for F, leading to an agile and robust optimization algorithm -- Ongoing work addresses the fitting of free-form parametric surfaces to SÍtem Tuning of Adaptive Weight Depth Map Generation Algorithms Exploratory Data Analysis and Design of Computer Experiments (DOCE)(Springer Verlag, 2013-09) Acosta, Diego; Congote, John; Barandiaran, Iñigo; Ruíz, Óscar; Hoyos, Alejandro; Graña, Manuel; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEIn depth map generation algorithms, parameters settings to yield an accurate disparity map estimation are usually chosen empirically or based on un planned experiments -- Algorithms' performance is measured based on the distance of the algorithm results vs. the Ground Truth by Middlebury's standards -- This work shows a systematic statistical approach including exploratory data analyses on over 14000 images and designs of experiments using 31 depth maps to measure the relative inf uence of the parameters and to fine-tune them based on the number of bad pixels -- The implemented methodology improves the performance of adaptive weight based dense depth map algorithms -- As a result, the algorithm improves from 16.78% to 14.48% bad pixels using a classical exploratory data analysis of over 14000 existing images, while using designs of computer experiments with 31 runs yielded an even better performance by lowering bad pixels from 16.78% to 13%Ítem Tuning of adaptive weight depth map generation algorithms: Exploratory data analysis and design of computer experiments (DOCE)(SPRINGER, 2013-09-01) Acosta, Diego; Barandiaran, Inigo; Congote, John; Ruiz, Oscar; Hoyos, Alejandro; Grana, Manuel; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEIn depth map generation algorithms, parameters settings to yield an accurate disparity map estimation are usually chosen empirically or based on unplanned experiments. Algorithms' performance is measured based on the distance of the algorithm results vs. the Ground Truth by Middlebury's standards. This work shows a systematic statistical approach including exploratory data analyses on over 14000 images and designs of experiments using 31 depth maps to measure the relative influence of the parameters and to fine-tune them based on the number of bad pixels. The implemented methodology improves the performance of adaptive weight based dense depth map algorithms. As a result, the algorithm improves from 16.78 to 14.48 % bad pixels using a classical exploratory data analysis of over 14000 existing images, while using designs of computer experiments with 31 runs yielded an even better performance by lowering bad pixels from 16.78 to 13 %. © 2012 Springer Science+Business Media, LLC.