1. Adaptive Streaming and Rendering of Large Terrains: a Generic Solution WSCG 2009 Raphaël Lerbour Jean-Eudes Marvie Pascal Gautron THOMSON R&D, Rennes, France

2. 2 Objectives Render large remote terrain datasets – Applications: GPS, games, weather… – 2D maps of samples: elevation (relief) and color – Gigabytes of data On multiple target devices and networks – Desktop PCs, handhelds… – Cannot transmit or display the dataset as a whole With good interactivity – Unpredicted user viewpoint moves – Rendering quality and speed requirements

3. 3 Overview Solutions – Network limitations: adaptive client-server streaming – Graphics hardware limitations: adaptive rendering We propose – A generic system for adaptive streaming and rendering – Single data structure suited for both parts – Favor speed from one end to the other

4. 4 Adaptive Streaming and Rendering of Large Terrains: a Generic Solution Data Structure Measure of importance Adaptive streaming Adaptive rendering

5. 5 Multi-resolution grid of square blocks of samples – Can be progressively loaded as a tree, starting with the root – Hierarchical block selection  minimize amount of rendered blocks Blocks have levels of detail (LOD) of increasing resolution – Adaptive LOD selection  minimize amount of structure operations Data structure

6. 6 No data redundancy – LODs of a block share data (common sample array) – Parent and children share one LOD (local copy when split/merge) New LOD: samples interleaved between existing ones – Possible to render a block with not all LODs loaded – Possible to render a block and load one of its LODs in parallel

7. 7 Adaptive Streaming and Rendering of Large Terrains: a Generic Solution Data Structure Measure of importance Adaptive streaming Adaptive rendering

8. 8 Measure of importance The base for adaptivity in both streaming and rendering – Importance represents desired quality for a block – We select LODs using importance thresholds Any formula may be used – Based on application – Typical variables: Distance from viewpoint Area Roughness

9. 9 Adaptive Streaming and Rendering of Large Terrains: a Generic Solution Data Structure Measure of importance Adaptive streaming Adaptive rendering

10. 10 Adaptive streaming Pre-computed server database for minimal activity – Only one file read per LOD request – File position for any LOD computed in constant time Data are transmitted “as-is” – Conversion (ex: elevation  3D vertices) on the client – Less data transmitted (quantization) – Same server and data with any client type We always transmit the most important data – Solution implicitly adapts to the network speed – Rendering quality constantly improves 0 s 10 s 40 s

11. 11 Adaptive streaming Potential LOD requests come with an importance value Restricted number of pending requests – Potential request with highest importance is transmitted to server – Others need to update their importance for next time – At reception, another request can be transmitted Server Requests management Network Client Adaptive streaming Adaptive rendering Rendering system Partial database Complete database Importance New LOD Request Reply (data)

12. 12 Adaptive Streaming and Rendering of Large Terrains: a Generic Solution Data Structure Measure of importance Adaptive streaming Adaptive rendering

13. 13 Adaptive rendering Client database: incomplete tree of blocks – Dynamic and asynchronous update operations – Data on all leaves  entire terrain can be rendered User selects desired rendering speed – Adaptive “quality factor” in importance formula – Importance triggers update operations 50 fps 100 fps 150 fps

14. 14 At each frame, we first: – Hierarchically cull invisible blocks – Compute importance to select a LOD for each block Then we trigger update operations Finally, we render visible leaves at selected LOD – With pre-computed masks to extract LOD samples Adaptive rendering LOD0 Importance LOD1 LOD0 usedLOD1 requested, LOD0 used SplitMergeLOD1 usedChildren used

15. 15 Application: 3D rendering LOD masks as triangle strips – Applied directly in hardware, no additional data copy Streamed data: elevation and color values – Bounded “flat” terrains: relative to a plane – Planets: relative to an ellipsoid Rendered data: textured 3D polygonal models

16. 16 Video

17. 17 Adaptive Streaming and Rendering of Large Terrains: a Generic Solution Contributions – Single data structure, generic mechanisms – Any network and rendering speeds – Any terrain data and rendering routines – Low CPU overhead Future work – Rendering optimizations – Validate the solution on handheld devices – Areas with different maximum resolution Acknowledgements – Kadi Bouatouch, IRISA