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Utilizing a discrete global grid system for handling point clouds with varying locations, times, and levels of detail / Neeraj Sirdeshmukh in Cartographica, vol 54 n° 1 (Spring 2019)  

Public [article]  inCartographica > vol 54 n° 1 (Spring 2019) . - pp 4 - 15 Titre : Utilizing a discrete global grid system for handling point clouds with varying locations, times, and levels of detail Type de document : Article/Communication Auteurs : Neeraj Sirdeshmukh, Auteur ; Edward Verbree, Auteur ; Peter J. M. Van Oosterom, Auteur ; Stella Psomadaki, Auteur ; Martin Kodde, Auteur Année de publication : 2019 Article en page(s) : pp 4 - 15 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] base de données localisées [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] indexation spatiale [Termes IGN] projection [Termes IGN] semis de points [Termes IGN] système de coordonnées [Termes IGN] système de grille globale discrète [Termes IGN] visualisation de données [Termes IGN] zoom Résumé : (Auteur) Discrete global grid systems (DGGSs) have emerged in recent years as a new specification for working with global heterogeneous data sets in a Digital Earth framework. Point clouds originating from different sources usually have varying initial characteristics. This research aims to analyze to what extent a DGGS can be used to handle point clouds having varying coordinate systems, acquired at different levels of detail (densities), and at different times in the creation of a global map of point clouds. DGGSs, which are currently limited to a 2D (surface) space, are extended into 3D and 4D spaces to fully harness the multidimensional nature of point clouds. A continuous spatial indexing strategy, based on a space-filling curve, is then developed on an ellipsoidal model of the Earth and used to efficiently cluster and retrieve DGGS-based point clouds stored in a database. Finally, the queried points are visualized in a Web browser. The hierarchical, multi-resolution nature of a DGGS is exploited to achieve a variable-scale smooth-zoom visualization. The challenges and opportunities of point cloud integration in a DGGS are presented. Numéro de notice : A2019-433 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart.54.1.2018-0009 Date de publication en ligne : 28/03/2019 En ligne : https://doi.org/10.3138/cart.54.1.2018-0009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92759 [article]

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Dense image matching / Martin Kodde in GIM international, vol 30 n° 1 (January 2016)

Public [article]  inGIM international > vol 30 n° 1 (January 2016) . - pp 28 -29 Titre : Dense image matching Type de document : Article/Communication Auteurs : Martin Kodde, Auteur Année de publication : 2016 Article en page(s) : pp 28 -29 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] accentuation d'image [Termes IGN] données massives [Termes IGN] semis de points [Termes IGN] vision par ordinateur Résumé : (éditeur) Point clouds are increasingly a prime data source for 3D information. For many years, Lidar systems have been the primary way to create point clouds. More recently, advances in the field of computer vision have allowed for the generation of detailed and reliable point clouds from images - not only from traditional aerial photographs but also from uncalibrated photos from consumer-grade cameras. Dense image matching is the powerful technology underpinning this development. Numéro de notice : A2016-015 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79347 [article]