1. CS 551 / 645: Introductory Computer Graphics
General Occlusion Culling
David Luebke /24/2019

2. Administrivia Questions on assignment 4?
Class Thursday: guest lecture by Professor Brogan
David Luebke /24/2019

3. Recap: Cells & Portals
An example:
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4. Recap: Cells & Portals A D E F B C G H A E B C D F G H

5. Recap: Cells & Portals A D E F B C G H A E B C D F G H

6. Recap: Cells & Portals A D E F B C G H A E B C D F G H

7. Recap: Cells & Portals A D E F B C G H A E B C D F G H

8. Recap: Cells & Portals A D E F B C G H A E B C D F G H

9. Recap: Cells & Portals A D E ? F B C G H A E B C D F G ? H

10. Recap: Cells & Portals A D E X F B C G H A E B C D F G X H

11. Recap: Cells & Portals
View-independent solution: find all cells a particular cell could possibly see:
C can only see A, D, E, and H A D H F C B E G A D E H

12. Recap: Cells and Portals
Good solution for most architectural or urban models
Use the simplest algorithm that suffices for your needs:
pfPortals-style algorithm: view-dependent solution, reasonably tight PVS, no preprocess necessary
Teller-style algorithm: tighter PVS, somewhat more complex, can provide view-independent solution for prefetching
David Luebke /24/2019

13. General Occlusion Culling
When cells and portals don’t work…
Trees in a forest
A crowded train station
Need general occlusion culling algorithms:
Aggregate occlusion
Dynamic scenes
Non-polygonal scenes (?)
David Luebke /24/2019

14. General Occlusion Culling
I’ll discuss two algorithms:
Hierarchical Z-Buffer
Ned Greene, SIGGRAPH 93
Hierarchical Occlusion Maps
Hansong Zhang, SIGGRAPH 97
David Luebke /24/2019

15. Hierarchical Z-Buffer
Replace Z-buffer with a Z-pyramid
Lowest level: full-resolution Z-buffer
Higher levels: each pixel represents the maximum depth of the four pixels “underneath” it
Basic idea: hierarchical rasterization of the polygon, with early termination where polygon is occluded
David Luebke /24/2019

16. Hierarchical Z-Buffer
Idea: test polygon against highest level first
If polygon is further than distance recorded in pixel, stop--it’s occluded
If polygon is closer, recursively check against next lower level
If polygon is visible at lowest level, set new distance value and propagate up
David Luebke /24/2019

17. Hierarchical Z-Buffer
Z-pyramid exploits image-space coherence:
Polygon occluded in a pixel is probably occluded in nearby pixels
HZB also exploits object-space coherence
Polygons near an occluded polygon are probably occluded
David Luebke /24/2019

18. Hierarchical Z-Buffer
Exploiting object-space coherence:
Subdivide scene with an octree
All geometry in an octree node is contained by a cube
Before rendering the contents of a node, “render” the faces of its cube (query the Z-pyramid)
If cube faces are occluded, ignore the entire node
David Luebke /24/2019

19. Hierarchical Z-Buffer
HZB can exploit temporal coherence
Most polygons affecting the Z-buffer last frame will affect Z-buffer this frame
HZB also operates at max efficiency when Z-pyramid already built
So start each frame by rendering octree nodes visible last frame
David Luebke /24/2019

20. Hierarchical Z-Buffer: Discussion
HZB needs hardware support to be really competitive
Hardware vendors haven’t bought in:
Z-pyramid (and hierarchies in general) unfriendly to hardware
Unpredictable Z-query times generate bubbles in rendering pipe
But there is a promising trend…
David Luebke /24/2019

21. Hierarchical Z-Buffer
Hardware beginning to support Z-query operation
Allows systems to exploit:
Object-space coherence (bounding boxes)
Temporal coherence (last-rendered list)
Systems I’m aware of:
HP Visualize-fx graphics
SGI Visual Workstation products
An aside: applies to cell-portal culling!
David Luebke /24/2019

22. Hierarchical Occlusion Maps
A more hardware-friendly general occlusion culling algorithm
Two major differences from HZB:
Separates occluders from occludees
Decouples occlusion test into an depth test and a overlap test
David Luebke /24/2019

23. Hierarchical Occlusion Maps
Occluders versus occludees:
Blue parts: occluders Red parts: occludees
David Luebke /24/2019

24. Hierarchical Occlusion Maps
Depth versus overlap:
View
Point Z X Y
Depth + Overlap = Occlusion
David Luebke /24/2019

25. Hierarchical Occlusion Maps
Representation of projection for overlap test: occlusion map
Corresponds to a screen subdivision
Records average opacity per partition
Generate by rendering occluders
Record pixel opacities (== coverage)
David Luebke /24/2019

26. Occlusion Maps
Rendered Image
Occlusion Map
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27. Occlusion Map Pyramid
64 x 64
32 x 32
16 x 16
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28. Occlusion Map Pyramid
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29. Occlusion Map Pyramid Analyzing cumulative projection:
A hierarchical occlusion map (HOM)
Generate by recursive averaging (l.p.f.)
Records average opacities for blocks of multiple pixels, representing occlusion at multiple resolutions
Construction can be accelerated by texture hardware
David Luebke /24/2019

30. Overlap Tests
Query: is projection of occludee inside cumulative projection of occluders?
Cumulative projection: occlusion pyramid
Ocludee projection: expensive in general
Overestimate ocludee with 3-D bounding box
Overestimate projection of 3-D bounding box with 2-D bounding rectangle in screen-space
David Luebke /24/2019

31. Overlap Tests Hierarchical structure enables some optimizations:
Predictive rejection
Terminate test when it must fail later
Conservative rejection
The transparency threshold
Aggressive Approximate Culling
Ignore objects barely visible through holes
The opacity threshold
David Luebke /24/2019

32. Aggressive Approximate Culling1 2 3 4
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33. Hierarchical Occlusion Maps
Not discussed here:
Depth test
Depth estimation buffer
Modified Z-buffer
Selecting occluders
For more details, see attached excerpt from Hansong Zhang’s dissertation
David Luebke /24/2019

34. HOM: Discussion
Provides a robust, general, hardware-friendly occlusion culling algorithm
Supports dynamic scenes
Supports non-polygonal geometry
Not many hardware assumptions
David Luebke /24/2019

35. HOM: Discussion Efficient coding, careful tuning a must
Fairly high per-frame overhead
Needs high depth complexity, good occluder selection to be worthwhile
UNC’s MMR system: HOM used maybe 5% of the time
David Luebke /24/2019

36. Visibility Culling: Discussion
When is visibility culling worthwhile?
When scene has high depth complexity
Examples: architectural walkthroughs, complex CAD assemblies, dense forest
Non-examples: terrain, single highly-tesselated object (e.g., a radiositized room)
David Luebke /24/2019

37. Visibility Culling: Discussion
How does visibility culling compare to:
Level-of-detail:
Reduces geometry processing
Helps transform-bound apps
Visibility culling:
Reduces geometry and pixel processing
Helps transform- and fill rate-bound apps
Texture / Image representations:
Incurs texture/image processing costs
David Luebke /24/2019

38. Visibility Culling: Discussion
How does visibility culling interact with level of detail?
Fairly seamless integration; generally a win
One issue: visibility of simplified model may differ from original model; requires some care
LODs can speed up occluder selection and rendering
David Luebke /24/2019

39. Visibility Culling: Discussion
How does visibility culling interact with texture and image-based representations?
Texture/image reps generally replace far-field geometry
Involves an implicit occlusion culling step
Reduces scene depth complexity, decreasing the utility of visibility culling
If near-field geometry still includes complex heavily-occlusive assemblies, still a win
David Luebke /24/2019

40. Visibility Culling: Discussion
How much culling effort is appropriate?
Cells and portals: relatively cheap, with large potential speedups
Hierarchical occlusion maps: relatively costly, carefully weigh potential gains
Multiple processors allow much more aggressive culling calculation
Pipelining culling calculations, Performer-style, lets cull time = render time
Tradeoff: one frame increased latency
David Luebke /24/2019

41. Summary The basic, very powerful idea:
Rapidly compute a potentially visible set
Let hardware handle the rest
For many scenes, visibility culling is a simple way to get huge speedups
View-frustum culling always a must
For scenes with high depth complexity, occlusion culling can be a big win
David Luebke /24/2019

42. Summary
Architectural models: visibility is practically a solved problem
Cells and portals work well
Cull-box portal culling: simple, fast
Line-stabbing: elegant, powerful
David Luebke /24/2019

43. Summary
Occlusion culling of general models: still a largely open problem
Important issues:
Dynamic scenes
Aggregate occlusion effects
David Luebke /24/2019

44. Summary General occlusion culling algorithms: Hierarchical Z-buffer:
A simple, truly elegant algorithm
But doesn’t seem amenable to hardware
Hierarchical occlusion maps:
More complicated, difficult to code & tune
Better suited to current hardware
Lends itself well to aggressive culling
Fairly high overhead, only worthwhile with high depth complexity
David Luebke /24/2019

45. The End
Questions?
David Luebke /24/2019