Distributed visualization of terrain models
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Transcript of Distributed visualization of terrain models
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Applied Mathematics
Distributed visualization of terrain models
How to get the whole world
into a coffee mug...
Rune Aasgaard
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Where to put the workload?
Do everything at the server Requires a powerful server... …and fast network connection... ...but simple client.
Render in the client Reduces load on server and network… …smooth interactive movement actually possible… …but requires a smart and complex client... …and more sophisticated hardware.
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Where to put the data?
Client terrain database Near graphics system Fast updating from server data Limited size Some support for simple analysis
Server terrain database Huge data volume Fast query access No traversal of data Integration of new and improved data sets?
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Level-of-Detail Triangulation
Consists of: A coarse base triangulation: T0
A set of refinement operations: Ti
Results in: A set of triangulations: Ti
View dependent expansion of client data structures: Only show what is necessary for generating an image Use screen-space error tolerance Approximation error estimates for each refinement operation
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Client data structures
Should support the graphics system
Triangle strips 3D coordinates Surface normals Texture coordinates Map to a set of texture tiles
Portability - Java and Java3D
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Client data structures
Update with data from server
Start with coarse base triangulation Request data from server when:
Area becomes visible More detail is required (viewpoint moved in)
Reduce to coarser level when: Area becomes invisible Less detail is required (viewpoint moved out)
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Server data structures
Can be huge!
Whole earth, 30” grid (DTED Level 0): 933.120.000 points! Whole earth, 3” grid (DTED Level 1): 93.312.000.000
points! Luckily, 2/3 of the earth is ocean Major parts of the land is relatively flat Can benefit from data simplification and compression
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Server data structures
Server responds to client requests: in: Position out: Elevation and Elevation approximation error
Queries are expected to be: chunked localized in area and resolution level
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Binary Triangle Trees
Hierarchy of right-isosceles triangles Related to Lindstrom triangulations and the ROAM
algorithm
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Binary Triangle Trees
Simple data structures simplifies network streaming
Regular refinement pattern fits well with texture tiles simple integer coordinates maps easily to regular quad trees
But…. requires more triangles for representing complex objects than
irregular triangulations
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Approximation error spheres
One sphere for each vertex
Radius = Approximation error / angular resolution
If the viewpoint is inside sphere, display vertex
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Zooming in - Scandinavia
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Zooming in - Scandinavia
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Zooming in - The Oslo fjord
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Zooming in - The Oslo fjord
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Zooming in - Tønsberg
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Zooming in - Tønsberg
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San Francisco - bay area
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Islands in the sun
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Oslo fjord - elevation color coding
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Oslo fjord - elevation color coding