Isbn: 9783668031500 - visualization of large unstructured grids. efficient point and cell location (11 risultati)

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  • Lingua: Inglese

    Editore: Grin Verlag, 2015

    3668031509 / 9783668031500

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    Editore: Grin Verlag 8/18/2015, 2015

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    Paperback or Softback. Condizione: New. Visualization of Large Unstructured Grids. Efficient Point and Cell Location. Book.

  • Lingua: Inglese

    Editore: Grin Verlag, 2015

    3668031509 / 9783668031500

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  • Lingua: Inglese

    Editore: Grin Verlag, 2015

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  • Lingua: Inglese

    Editore: Grin Verlag, 2015

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  • Lingua: Inglese

    Editore: Grin Verlag, 2015

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  • Lingua: Inglese

    Editore: GRIN Verlag, 2015

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Seminar paper from the year 2013 in the subject Engineering - Computer Engineering, grade: 1.0, University of Heidelberg (Computer Graphics and Visualization), course: Seminar Computer Vision, language: English, abstract: Visualization of large data sets, especially the visualization of unstructured grids, is a challenge due to the unstructured nature of the data which oftentimes causes large overheads in memory as well as performance problems on large grids. Problems emerge because existing solutions generally presuppose properties like uniform point distributions for datasets which are usually not existent in unstructured grids. These issues become particularly problematic on large grids since the existing solutions, if they work at all for unstructured grids, do not scale well. In this paper I will present two innovative approaches to visualization in large, unstructured grids. The first approach was developed by Max Langbein, Gerik Scheuermann and Xavier Tricoche. It makes use of cell adjacency and a complete adaptive k-d tree and utilizes ray shooting to locate points for visualization. The second approach was developed by Christoph Garth and Kenneth I. Joy. They use an innovative data structure, the celltree which is based on a bounding interval hierarchy, in order to narrow down the number of cells that conceivably contain points for visualization. Both approaches present memoryecient and performant solutions for visualizing large unstructured grids, the approach of Garth and Joy further focuses on numerical robustness. The main difference between the two papers is that the work of Garth and Joy designs a data structure based on points and attempts to narrow down the number of cell candidates and subsequently performs a simple check for inclusion, whereas in the work of Langbein et al. the data structure design is based on the cells and uses ray tracing after making an educated guess for a cell close to the searched point. In other words, Garth and Joy present an approach to cell location, Langbein et al. present an approach for point location.

  • Lingua: Inglese

    Editore: Grin Verlag, 2015

    3668031509 / 9783668031500

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    Condizione: New. Print on Demand pp. 20.

  • Lingua: Inglese

    Editore: GRIN Verlag Aug 2015, 2015

    3668031509 / 9783668031500

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Seminar paper from the year 2013 in the subject Engineering - Computer Engineering, grade: 1.0, University of Heidelberg (Computer Graphics and Visualization), course: Seminar Computer Vision, language: English, abstract: Visualization of large data sets, especially the visualization of unstructured grids, is a challenge due to the unstructured nature of the data which oftentimes causes large overheads in memory as well as performance problems on large grids. Problems emerge because existing solutions generally presuppose properties like uniform point distributions for datasets which are usually not existent in unstructured grids. These issues become particularly problematic on large grids since the existing solutions, if they work at all for unstructured grids, do not scale well. In this paper I will present two innovative approaches to visualization in large, unstructured grids. The first approach was developed by Max Langbein, Gerik Scheuermann and Xavier Tricoche. It makes use of cell adjacency and a complete adaptive k-d tree and utilizes ray shooting to locate points for visualization. The second approach was developed by Christoph Garth and Kenneth I. Joy. They use an innovative data structure, the celltree which is based on a bounding interval hierarchy, in order to narrow down the number of cells that conceivably contain points for visualization. Both approaches present memoryecient and performant solutions for visualizing large unstructured grids, the approach of Garth and Joy further focuses on numerical robustness. The main difference between the two papers is that the work of Garth and Joy designs a data structure based on points and attempts to narrow down the number of cell candidates and subsequently performs a simple check for inclusion, whereas in the work of Langbein et al. the data structure design is based on the cells and uses ray tracing after making an educated guess for a cell close to the searched point. In other words, Garth and Joy present an approach to cell location, Langbein et al. present an approach for point location. 20 pp. Englisch.

  • Lingua: Inglese

    Editore: GRIN Verlag, GRIN Verlag Aug 2015, 2015

    3668031509 / 9783668031500

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Seminar paper from the year 2013 in the subject Engineering - Computer Engineering, grade: 1.0, University of Heidelberg (Computer Graphics and Visualization), course: Seminar Computer Vision, language: English, abstract: Visualization of large data sets, especially the visualization of unstructured grids, is a challenge due to the unstructured nature of the data which oftentimes causes large overheads in memory as well as performance problems on large grids. Problems emerge because existing solutions generally presuppose properties like uniform point distributions for datasets which are usually not existent in unstructured grids. These issues become particularly problematic on large grids since the existing solutions, if they work at all for unstructured grids, do not scale well. In this paper I will present two innovative approaches to visualization in large, unstructured grids. The first approach was developed by Max Langbein, Gerik Scheuermann and Xavier Tricoche. It makes use of cell adjacency and a complete adaptive k-d tree and utilizes ray shooting to locate points for visualization. The second approach was developed by Christoph Garth and Kenneth I. Joy. They use an innovative data structure, the celltree which is based on a bounding interval hierarchy, in order to narrow down the number of cells that conceivably contain points for visualization. Both approaches present memoryecient and performant solutions for visualizing large unstructured grids, the approach of Garth and Joy further focuses on numerical robustness. The main difference between the two papers is that the work of Garth and Joy designs a data structure based on points and attempts to narrow down the number of cell candidates and subsequently performs a simple check for inclusion, whereas in the work of Langbein et al. the data structure design is based on the cells and uses ray tracing after making an educated guess for a cell close to the searched point. In other words, Garth and Joy present an approach to cell location, Langbein et al. present an approach for point location.Books on Demand GmbH, Überseering 33, 22297 Hamburg 20 pp. Englisch.

  • Lingua: Inglese

    Editore: GRIN Verlag, 2015

    3668031509 / 9783668031500

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    Taschenbuch. Condizione: Neu. Visualization of Large Unstructured Grids. Efficient Point and Cell Location | Philipp Güth | Taschenbuch | 20 S. | Englisch | 2015 | GRIN Verlag | EAN 9783668031500 | Verantwortliche Person für die EU: GRIN Publishing GmbH, Waltherstr. 23, 80337 München, info[at]grin[dot]com | Anbieter: preigu Print on Demand.