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3D visualization of multivariate data / Harald Sanftmann (2012)  

Public Titre : 3D visualization of multivariate data Type de document : Thèse/HDR Auteurs : Harald Sanftmann, Auteur ; Daniel Weiskopf, Directeur de thèse ; H. Hauser, Directeur de thèse Editeur : Stuttgart : University of Stuttgart Année de publication : 2012 Importance : 157 p. Format : 21 x 30 cm Note générale : Bibliographie Von der Fakultät Informatik, Elektrotechnik und Informationstechnik der Universität Stuttgart zur Erlangung der Würde eines Doktors der Naturwissenschaften, genehmigte Abhandlung Langues : Anglais (eng) Descripteur : [Termes IGN] anaglyphe [Termes IGN] analyse multivariée [Termes IGN] apprentissage profond [Termes IGN] arbre de décision [Termes IGN] éclairement lumineux [Termes IGN] restitution numérique [Termes IGN] semis de points [Termes IGN] traitement de semis de points [Termes IGN] visualisation 3D [Vedettes matières IGN] Géovisualisation Index. décimale : THESE Thèses et HDR Résumé : (auteur) Nowadays large amounts of data are organized in tables, especially in relational databases where the rows store the data items to which multiple attributes are stored in the columns. Information stored this way, having multiple (more than two or three) attributes, can be treated as multivariate data. Therefore, visualization methods for multivariate data have a large application area and high potential utility. This thesis focuses on the application of 3D scatter plots for the visualization of multivariate data. When dealing with 3D, spatial perception needs to be exploited, by effectively using depth cues to convey spatial information to the user. To improve the presentation of individual 3D scatter plots, a technique is presented that applies illumination to them, thus using the shape-from-shading depth cue. To enable the analysis not only of 3D but of multivariate data, a novel technique is introduced that allows the navigation between 3D scatter plots. Inspecting the large number of 3D scatter plots that can be projected from a multivariate data set is very time consuming. The analysis of multivariate data can benefit from automatic machine learning approaches. A presented method uses decision trees to increase the speed a user can gain an understanding of the multivariate data at no extra cost. Stereopsis can also support the display of 3D scatter plots. Here an improved anaglyph rendering technique is presented, significantly reducing ghosting artifacts. The technique is not only applicable for information visualization, but for general rendering or to present stereoscopic image data. Some information visualization algorithms require high computation time. Many of these algorithms can be parallelized to run interactively. A framework that supports the parallelization on shared and distributed memory systems is presented. Note de contenu : Introduction 1 - The Notion of 3D in Information Visualization 2 - Improving Depth Perception of 3D Scatter Plots 3 - 3D Scatter Plot Navigation 4 - Visualization with Decision Trees 5 - Anaglyph Stereo without Ghosting 6 - Distributed Visualization Conclusion and Outlook Numéro de notice : 21571 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Thèse étrangère Note de thèse : PhD dissertation : Informatik, Elektrotechnik und Informationstechnik : Universität Stuttgart : 2012 DOI : 10.18419/opus-6401 En ligne : http://doi.org/10.18419/opus-6401 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90561