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Pose imagery and automated three-dimensional modeling of urban environments / Satyan R. Coorg (1998)

Public Titre : Pose imagery and automated three-dimensional modeling of urban environments Type de document : Thèse/HDR Auteurs : Satyan R. Coorg, Auteur Editeur : Cambridge [Massachusetts - Etats-Unis] : MIT Press Année de publication : 1998 Importance : 121 p. Format : 21 x 30 cm Note générale : bibliographie Thesis submitted to the Department of Electrical Engineering and Computer Science in Partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] estimation de pose [Termes IGN] extraction automatique [Termes IGN] façade [Termes IGN] modélisation 3D [Termes IGN] monde virtuel [Termes IGN] mosaïque d'images [Termes IGN] positionnement par GPS [Termes IGN] vision par ordinateur [Termes IGN] zone urbaine Résumé : (auteur) Three-dimensional (3-D) modeling of urban environments has numerous applications, including virtual environments, urban planning, and physical simulation. Construct-ing 3-D models from photographs (images) is thus an important area of research in computer vision, and increasingly, computer graphics. However, despite many years of research, a system that automatically recovers realistic 3-D models remains elusive; most practical systems require significant human input. Unlike automatic algorithms, human-assisted systems are not scalable, both in terms of the number of images processed and the complexity of the generated 3-D model. This thesis describes novel techniques to automatically extract textured 3-D mod-els of urban environments from pose imagery, i.e., images annotated with camera position and orientation in a single global coordinate system. Physical instruments (e.g., surveying, Global Positioning System (GPS), inertial sensors, etc.) are used to provide accurate initial pose estimates to the proposed algorithms. As these es-timates are not perfect, I first describe two optimization techniques that refine pose estimates using information present in the images: spherical mosaicing recovers rel-ative rotations between images taken from a single position, and mosaic registration accurately locates mosaics in a global coordinate system. Next, I describe an algo-rithm that extracts vertical facades from mosaics annotated with accurate pose. The algorithm employs horizontal line segments to detect likely facade orientations and locates these facades using a space-sweep technique. Textures are robustly computed for the facades by combining information from several mosaics using median statistics. I present results for a large pose image dataset (consisting of about four thousand images taken from eighty-one positions) of an urban office complex. These techniques were successful in recovering all significant vertical facades in the complex, as well as several neighboring facades. Numéro de notice : 25546 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Thesis : Electrical Engineering and Computer Science : Cambridge : Etats-Unis : 1998 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94426

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
25546-01	K321	Livre	Saint-Mandé	Dépôt en unité	Exclu du prêt