Issues in Terrain Visualization for Environmental Monitoring Applications

1. Issues in Terrain Visualization for Environmental Monitoring Applications Ricardo Veguilla veguilla@ece.uprm.edu Nayda G. Santiago nayda.santiago@ece.uprm.edu Domingo A. Rodriguez domingo@ece.uprm.edu Electrical and Computer Engineering Department University of Puerto Rico, Mayagüez Campus June 23, 2006

2. Raw Data Servers Computed Data Servers WALSAIP WALSAIP: Wide Area Large Scale Automated Information Processing INTERNET Data Representation Systems Computational Signal Processing Systems Signal Data Post-processing Information Rendering Systems Signal Conditioning System Sensor Array Structures Pre-processing Stage Processing Stage Post-processing Stage

3. WALSAIP-VTE (Visual Terrain Explorer) WALSAIP Cyber-Infrastructure Information Rendering System (Visualization) Automated Data Processing Data Acquisition

4. Data size, complexity, and performance • 3D visualization is computationally expensive • We want to visualize large, complex geometrical models • Critical for interactive terrain visualization due to the sheer size of the data sets

5. Level of Detail

6. Level of Detail (LOD) • Premise: It is inefficient to use many polygons to render object that will only contribute to a few pixels of the rendered scene. • Conclusion: Use less detail for small, distant portions of the scene. • Approach: Use geometric simplification operations to eliminate redundant information while satisfying both performance and visual accuracy constrains.

7. Our Goal Review available terrain rendering LOD techniques, with interested in: • How to exploit video card (GPU) processing capabilities • Handling data larger than available memory (out of core, distributed computing) • Identify best approach for a future implementation of the VTE

8. Basic Components • The initial mesh: A polygonal representation of the terrain at either the minimum resolution level (base mesh) or the maximum resolution level (full mesh) • Updates operations: Operation which simplify or refine a mesh.

9. Characteristics of LOD Algorithms • LOD Granularity • LOD Distribution • Processing direction • Terrain Data Structure • LOD Data Structure

10. 76 polys 2,502 polys 69,451 polys 251 polys LOD granularity • Discrete LOD: finite set of pre-computed LODs • Continuous LOD: further simplifies discrete LODs to produce a continuous spectrum of detail 251 polys 69,451 polys N polys

11. LOD distribution • Uniform • View-dependent

12. Processing direction Top-down (refinement or subdivision algorithm) Bottom-up (simplification or decimation algorithm)

13. Terrain data structure Height fields (Regular) Triangulated Irregular Networks (Irregular)

14. LOD data structure Quadtree: a rectangular region recursively subdivided into four uniform quadrants. Bintree (Binary triangle tree) : a rectangular region is recursively subdivided into two triangles.

15. Survey of Algorithms

16. Approaches • Traditional Approach • 80’s • The basic unit is the triangle • Traditional LOD techniques generally aimed to produce the ideal level of detail • Modern Approach • 2000’s • Basic unit is the triangle cluster or patch • Concerned with maximizing GPU usage and minimizing CPU usage

17. Traditional Approach

18. Real-time, continuous LOD rendering of height fields • Using a quadtree with discrete LODS generated off-line top-down refinement bottom-up simplification

19. ROAM • Uses two ordered priority queues: one for split operations and the other for merge operations.

20. View-dependent Progressive Meshes • a TIN-based, view dependent terrain LOD algorithm • Continuous LOD is produce by recursively removing triangles from off-line generated blocks of terrain.

21. Modern Approach

22. Geometrical MipMapping Quadtree technique that work on blocks of uniform detail Simplification based on vertex removal Selection based on worst-case view parameters Eliminates cracks by changing vertex connectivity at the block boundary

23. Triangle cluster Techniques • Cluster: small triangle meshes optimized for GPU processing • Cluster are cached on the video card memory. • Hierarchy is used for view culling ACL Frustrum Occluded Cluster Inactive Cluster Visible Cluster Occluded Cluster ACL = Active Cluster List

24. Geometry Clipmap A multi-resolution mesh formed by combining nested concentric grids center about the view position Resulting view View culling

25. Conclusions • In Use of triangle cluster patches as basic rendering unit allow: • maximizing GPU usage* • better coupling of the geometry and the texture • out-of-core operation* • The ideal level of detail (an irregular mesh) is in compatible with GPU maximization (which require regular meshes) *points of interest for the WALSAIP-VTE project

26. LOD and WALSAIP WALSAIP Cyber-Infrastructure Automated Terrain LOD Generation Terrain Visualization Terrain Data Acquisition

27. WALSAIP-VTE - Status • Java and OpenGL implementation with LOD based on GeoMipMaps. • Future research on out-of-core data management for remote data acquisition

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30. Questions? • Ricardo Veguilla veguilla@ece.uprm.edu