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Point clouds for use in Building Information Models (BIM) / Robert Klinc in Geodetski vestnik, vol 65 n° 4 (December 2021 - February 2022)  

Public [article]  inGeodetski vestnik > vol 65 n° 4 (December 2021 - February 2022) . - pp 594 - 613 Titre : Point clouds for use in Building Information Models (BIM) Type de document : Article/Communication Auteurs : Robert Klinc, Auteur ; Uroš Jotanović, Auteur ; Klemen Kregar, Auteur Année de publication : 2021 Article en page(s) : pp 594 - 613 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canalisation [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction automatique [Termes IGN] modélisation 3D du bâti BIM [Termes IGN] mur [Termes IGN] qualité du modèle [Termes IGN] Revit [Termes IGN] semis de points [Termes IGN] traitement de semis de points Résumé : (Auteur) The use of point clouds in extracting data for building information modelling (BIM) has become common recently. Managers of older buildings are working to centralise information. Documentation about mechanical installations, plumbing, electricity, and previous interventions is often stored on scattered media, frequently still on paper. In the transformation of the material world into the digital world, the point cloud is the starting point, containing information about the material world obtained by various means such as photogrammetry, terrestrial or aerial laser scanning. Manual BIM modelling for management, maintenance and future use is a time-consuming and error-prone process. We would like to automate this process and avoid these errors. Recently, there have been developed an increasing number of stand-alone programmes and add-ons that provide automated, fast, and more accurate modelling based on point cloud data. In this paper, we present an investigation into the possibilities for automating the creation of BIM models from point cloud data. The result is a semi-automated process for modelling individual BIM elements, which we have tested on specific examples of modelling individual elements (walls, pipes, and columns). We note that despite the automation of the process, a high level of user interaction is still required to produce good quality models. Numéro de notice : A2021-931 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.15292/geodetski-vestnik.2021.04.594-613 Date de publication en ligne : 06/12/2021 En ligne : https://doi.org/10.15292/geodetski-vestnik.2021.04.594-613 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99410 [article]

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139-2021041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

The reliability of RANSAC method when estimating the parameters of geometric object / Tilen Urbančič in Geodetski vestnik, vol 60 n° 1 (March - May 2016)  

Public [article]  inGeodetski vestnik > vol 60 n° 1 (March - May 2016) . - pp 69 - 97 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] solide Résumé : (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 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
139-2016011	RAB	Revue	Centre de documentation	En réserve L003	Disponible