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Auteur Anja Vrecko |
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The reliability of RANSAC method when estimating the parameters of geometric object / Tilen Urbančič in Geodetski vestnik, vol 60 n° 1 (March - May 2016)
[article]
Titre : The reliability of RANSAC method when estimating the parameters of geometric object Type de document : Article/Communication Auteurs : Tilen Urbančič, Auteur ; Anja Vrecko, Auteur ; Klemen Kregar, Auteur Année de publication : 2016 Article en page(s) : pp 69 - 97 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Algorithmique
[Termes IGN] estimation des paramètres
[Termes IGN] méthode fiable
[Termes IGN] modèle mathématique
[Termes IGN] Ransac (algorithme)
[Termes IGN] résidu
[Termes IGN] solideRésumé : (Auteur) The RANSAC (RANdom SAmple Consensus) is often used to identify points belonging to the objects whose shape can be modeled with geometric primitives. These points, called inliers, are of great interest in some applications but often the goal is also to estimate the parameters of geometric shape and their accuracies. The quality of RANSAC results is rarely analyzed. The accuracies of estimated parameters are usually calculated based only on the residuals of inliers, selected by RANSAC, from a mathematical model. However, the analysis does not indicate if the right points were selected. The result of RANSAC depends on the random selection of the minimum number of points that uniquely describe a mathematical model; in the case of multiple repetitions of the method, the results are not necessarily the same. This paper presents an analysis of RANSAC reliability based on repeating the selection of points from the point cloud by RANSAC one hundred times. A standard deviation of one hundred parameter values is used to estimate the parameters’ accuracies. An analysis is made for three different examples of geometric objects: a sphere, a cone, and a plane. Finally, we suggest repeating the algorithm several times and checking the consistency of the results to obtain a more reliable estimation of parameters and their accuracies. Numéro de notice : A2016-175 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.15292/geodetski-vestnik.2016.01.69-97 En ligne : http://dx.doi.org/10.15292/geodetski-vestnik.2016.01.69-97 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80520
in Geodetski vestnik > vol 60 n° 1 (March - May 2016) . - pp 69 - 97[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 139-2016011 RAB Revue Centre de documentation En réserve L003 Disponible Digital Elevation Model from the best results of different filtering of a LiDAR point cloud / T. Podobnikar in Transactions in GIS, vol 16 n° 5 (October 2012)
[article]
Titre : Digital Elevation Model from the best results of different filtering of a LiDAR point cloud Type de document : Article/Communication Auteurs : T. Podobnikar, Auteur ; Anja Vrecko, Auteur Année de publication : 2012 Article en page(s) : pp 603 - 617 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] modèle numérique de surface
[Termes IGN] semis de pointsRésumé : (Auteur) The LiDAR point clouds captured with airborne laser scanning provide considerably more information about the terrain surface than most data sources in the past. This rich information is not simply accessed and convertible to a high quality digital elevation model (DEM) surface. The aim of the study is to generate a homogeneous and high quality DEM with the relevant resolution, as a 2.5D surface. The study is focused on extraction of terrain (bare earth) points from a point cloud, using a number of different filtering techniques accessible by selected freeware. The proposed methodology consists of: (1) assessing advantages/disadvantages of different filters across the study area, (2) regionalization of the area according to the most suitable filtering results, (3) data fusion considering differently filtered point clouds and regions, and (4) interpolation with a standard algorithm. The resulting DEM is interpolated from a point cloud fused from partial point clouds which were filtered with multiscale curvature classification (MCC), hierarchical robust interpolation (HRI), and the LAStools filtering. An important advantage of the proposed methodology is that the selected landscape and datasets properties have been more holistically studied, with applied expert knowledge and automated techniques. The resulting highly applicable DEM fulfils geometrical (numerical), geomorphological (shape), and semantic quality properties. Numéro de notice : A2012-513 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01332.x Date de publication en ligne : 10/10/2012 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01332.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31959
in Transactions in GIS > vol 16 n° 5 (October 2012) . - pp 603 - 617[article]