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Dynamic Mapping of Raster-Data For 3D Geovirtual Environments Matthias Trapp , Jürgen Döllner Hasso-Plattner-Institute, University of Potsdam, Germany 13 th  International Conference on Information Visualisation 14-17 July
motivation ,[object Object]
motivation ,[object Object],Preprocessing Time:  days-hours Preprocessing Time:  hours-minutes Preprocessing Time:  minutes
wrap-up: challenges & goals ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
overview: dynamic texture mapping ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
texture coordinate generation ,[object Object],[object Object],U V
color transfer functions ,[object Object],[object Object]
rendering at a glance ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],#Vertex #Mappings FPS without FPS with FPS loss (%) 1,040,503 3 10.41 9.87 5.19 41,032 4 52.88 51.20 3.18 61,756 27 156.10 27.94 82.10 6 4 1063.83 236.97 77.72 37,404 16 206.21 45.70 77.84 6 6 1075.27 110.54 89.72
application examples ,[object Object],Building category data Traffic frequency data Data Layer: Color Layer: Data Layer: Color Layer:
 
application examples ,[object Object],Landmark objects Landmark objects Route
 
application examples ,[object Object]
application examples ,[object Object]
conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
thank you... Contact: Matthias Trapp [email_address] Jürgen Döllner [email_address] Computer Graphics System Group www.hpi.uni-potsdam.de/3d Researchgroup 3D-Geoinformation www.3dgi.de

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Dynamic Mapping of Raster Data (IV 2009)

  • 1. Dynamic Mapping of Raster-Data For 3D Geovirtual Environments Matthias Trapp , Jürgen Döllner Hasso-Plattner-Institute, University of Potsdam, Germany 13 th International Conference on Information Visualisation 14-17 July
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  • 16. thank you... Contact: Matthias Trapp [email_address] Jürgen Döllner [email_address] Computer Graphics System Group www.hpi.uni-potsdam.de/3d Researchgroup 3D-Geoinformation www.3dgi.de

Editor's Notes

  1. Hello! Thank you very much for the introduction. Now, I‘d like to present a concept for dynamically mapping raster-data to complex 3D GeoVE [CLICK]
  2. The main idea of this projects is to use 3D GeoVE, such as 3D City and landscape models as scenery for visualizing information which maybe the result of a geo-analytics process. Such as these exemplary visualization, on which I‘ll focus later on. But, what exactly is the problem to achieve this within 3D geovirtual environments ? [CLICK]
  3. If you take a look on this picture of a 3D GeoVE, Pre-processing time Model + Textures So where is the problem? 3D GeoVE require
  4. So, let me wrap-up the challenges and goals of this project: To render large-scale geo data sets at interactive frame rates, usually a specific out-of-core render is necessary. Such renderer require pre-processed data. The time for pre-processing depends on the complexity and is often time consuming. So such approach cannot be used to incorporate time critical data. That‘s why we need to partially de-couple geometry and appreance.
  5. To achive this major goal we use dyanmic texture mapping A combination of texture coordinate generator, texture sampling and color transfer functions. In other words… texture coordinate geeration and enhanced multitexturing. So, our approach need at least three inputs: the 3D coordinate of a point to texture, data & color layer as well as the mapping parameterizations. The output is a final color. The data and color layers can be 1D/2D and 3D texture image, which function as mask, data values, or color gradient sfor the color mapping.
  6. For dynamic texture coordinate generation, we use projective texture mapping introduced by Cass Everitt in 2001. This is simply a vector-matrix multiplication using the 3D point-coordinates as input. As the projector matrix MP we use an orthogonal projection matrix since we can assume that 3D GeoVE at our scale can be approximated by a 3D plane. The projector matrix is adjusted using two vector as depicted on the right. [CLICK]
  7. The color transfer function component is inspired by Bruckner and describes the color mapping. It supports the standard blending operations For details on this topic I‘d like to refer to the paper and give only a simple example [CLICK]
  8. To implement our concept on modern consumer graphics hardware we have to extend the existing OpenGl/DirectX muti-texturing pipeline. We are able to render all mappings within a single rendering pass. All the work, is performed with a fragment shader program. The data and color layers are encode in texture arrays , some kind of 3D textures. The performance of our approach is fill-limited, i.e. the more fragments and mappings the more drops the FPS. [CLICK]
  9. Let me know focus on some selected application examples. The main field is the hierarchical mapping and combination of thematic raster data. In this example you can see two data layers [CLICK] combined using two masks and applied to a section of the virtual 3D city model of Berlin. The same works also for dynamic simulation data [CLICK].
  10. This is an pseudo examples that show two video data layers containing the results of fluid simulations. These both applied to an artificial city model. The blending modes of the color transfer functions results in violet color where the red and blue data overlaps. [CLICK]
  11. Our frame work can also be used for object and route highlighting to facilitate orientation and navigation in 3D geovirtual environments. Here, two types of landmarks [CLICK] , a navigation route with its start and end points, as well as the current position is visualized. The next video shows the creation process for such an visualization. [CLICK]
  12. First we load specifi data layers for the highlighting apperance. Then loading the position data for the landmark and change some appearance parameters.
  13. We further can use our concept to facilitate the creation of 3D digital maps by enhancing the 3D city models with symbolic annotations. The left inset shows the texture atlas of the used symbols. With our technique it becomes possible to dynamically adjust the symbols position, size and alignment. [CLICK]
  14. Finally, one can use our approach to easily implement 2D magic lenses. This examples use three mask layer, two geo-referenced input textures, and a set of symbols. The same setting can be used with different color mapping and blending functions.
  15. We present an extendable concept for dynamically mapping 2D raster-data to 3D geovirtual environments. It is based on projective texture mapping for dynamic texture coordinate generation and provides a fully hardware accelerated implementation that enables the interactive rendering for a high number of projective mappings. The major limitation of our approach is that it require the 3D GeoVEO to approximate by a 3D plane. For future work we concentrate on extending the existing color transfer function to enable complete style transfers. [CLICK]
  16. Thank you very much for your attention. I‘ll welcome any question you may have on this topic.