Darstellung großer graphischer Modelle : Methoden und Anwendungen

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dc.contributor Tübingen / Wilhelm-Schickard-Institut für Informatik / Arbeitsbereich Graphisch-Interaktive Systeme de_DE
dc.contributor.advisor Straßer, Wolfgang de_DE
dc.contributor.author Bartz, Dirk de_DE
dc.date.accessioned 2001-12-21 de_DE
dc.date.accessioned 2014-03-18T10:09:39Z
dc.date.available 2001-12-21 de_DE
dc.date.available 2014-03-18T10:09:39Z
dc.date.issued 2001 de_DE
dc.identifier.other 099866307 de_DE
dc.identifier.uri http://nbn-resolving.de/urn:nbn:de:bsz:21-opus-4333 de_DE
dc.identifier.uri http://hdl.handle.net/10900/48313
dc.description.abstract The size of datasets in scientific computing is rapidly increasing. This increase is caused by a boost of processing power in the past years, which in turn was invested in an increase of the accuracy and the size of the models. A similar trend enabled a significant improvement of medical scanners; more than 1000 slices of a resolution of 512x512 can be generated by modern scanners in daily practice. Even in computer-aided engineering typical models eas-ily contain several million polygons. Unfortunately, the data complexity is growing faster than the rendering performance of modern computer systems. This is not only due to the slower growing graphics performance of the graphics subsystems, but in particular because of the significantly slower growing memory bandwidth for the transfer of the geometry and image data from the main memory to the graphics accelerator. Large model visualization addresses this growing divide between data complexity and rendering performance. Most methods focus on the reduction of the geometric or pixel complexity, and hence also the memory bandwidth requirements are reduced. In this dissertation, we discuss new approaches from three different research areas. All approaches target at the reduction of the processing complexity to achieve an interactive visualization of large datasets. In the second part, we introduce applications of the presented ap-proaches. Specifically, we introduce the new VIVENDI system for the interactive virtual endoscopy and other applications from mechanical engineering, scientific computing, and architecture. de_DE
dc.description.abstract The size of datasets in scientific computing is rapidly increasing. This increase is caused by a boost of processing power in the past years, which in turn was invested in an increase of the accuracy and the size of the models. A similar trend enabled a significant improvement of medical scanners; more than 1000 slices of a resolution of 512x512 can be generated by modern scanners in daily practice. Even in computer-aided engineering typical models eas-ily contain several million polygons. Unfortunately, the data complexity is growing faster than the rendering performance of modern computer systems. This is not only due to the slower growing graphics performance of the graphics subsystems, but in particular because of the significantly slower growing memory bandwidth for the transfer of the geometry and image data from the main memory to the graphics accelerator. Large model visualization addresses this growing divide between data complexity and rendering performance. Most methods focus on the reduction of the geometric or pixel complexity, and hence also the memory bandwidth requirements are reduced. In this dissertation, we discuss new approaches from three different research areas. All approaches target at the reduction of the processing complexity to achieve an interactive visualization of large datasets. In the second part, we introduce applications of the presented ap-proaches. Specifically, we introduce the new VIVENDI system for the interactive virtual endoscopy and other applications from mechanical engineering, scientific computing, and architecture. en
dc.language.iso de de_DE
dc.publisher Universität Tübingen de_DE
dc.rights ubt-podok de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=de de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=en en
dc.subject.classification Graphik , Medizinische Informatik , Parallelverarbeitung de_DE
dc.subject.ddc 004 de_DE
dc.subject.other Darstellung großer graphischer Modelle , Verdeckungsrechnung , Virtuelle Endoscopie de_DE
dc.subject.other Large Model Visualization , Occlusion Culling , Virtual Endoscopy en
dc.title Darstellung großer graphischer Modelle : Methoden und Anwendungen de_DE
dc.title Large Model Visualization : Techniques and Applications en
dc.type Dissertation de_DE
dc.date.updated 1970-01-01 de_DE
dcterms.dateAccepted 2001-05-09 de_DE
utue.publikation.fachbereich Sonstige - Informations- und Kognitionswissenschaften de_DE
utue.publikation.fakultaet 7 Mathematisch-Naturwissenschaftliche Fakultät de_DE
dcterms.DCMIType Text de_DE
utue.publikation.typ doctoralThesis de_DE
utue.opus.id 433 de_DE
thesis.grantor 17 Fakultät für Informations- und Kognitionswissenschaften de_DE

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