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CS 445: Introduction to Computer Graphics David Luebke University of Virginia

Visibility: The Z-buffer Visibility Culling. CS 445: Introduction to Computer Graphics David Luebke University of Virginia. Admin. Grades for assignment 1 should be out Clipping assignment: how’s it going? Sample solution (partial) on web. Demo. Videos. Recap: Painter’s Algorithm.

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CS 445: Introduction to Computer Graphics David Luebke University of Virginia

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  1. Visibility: The Z-buffer Visibility Culling CS 445: Introduction to Computer Graphics David Luebke University of Virginia

  2. Admin • Grades for assignment 1 should be out • Clipping assignment: how’s it going? • Sample solution (partial) on web

  3. Demo • Videos

  4. Recap: Painter’s Algorithm • Simple approach: render the polygons from back to front, “painting over” previous polygons: • Draw blue, then green, then pink

  5. Recap: Painter’s Algorithm • Intersecting polygons present a problem • Even non-intersecting polygons can form a cycle with no valid visibility order: • Even without such a cycle, not obvious how to sort (ex: cube)

  6. Recap: Analytic Visibility Algorithms • Early visibility algorithms computed the set of visible polygon fragments directly, then rendered the fragments to a display: • Now known as analytic visibility algorithms

  7. Recap: Analytic Algorithms Worst Case • Minimum worst-case cost of computing the fragments for a scene composed of n polygons: O(n2) visible fragments

  8. Recap: Analytic Visibility Algorithms • So, for about a decade (late 60s to late 70s) there was intense interest in finding efficient algorithms for hidden surface removal • We’ll talk about two: • Binary Space-Partition (BSP) Trees • Warnock’s Algorithm

  9. Recap: BSP Trees • Binary Space Partition tree: organize all of space (hence partition)into a binary tree • Preprocess: overlay a binary tree on objects in the scene • Runtime: correctly traversing this tree enumerates objects from back to front • Idea: divide space recursively into half-spaces by choosing splitting planes • Splitting planes can be arbitrarily oriented • Notice: nodes are always convex

  10. Recap: BSP Trees 9 8 7 6 5 1 4 1 2 3 8 6 5 3 7 9 2 4

  11. Recap: BSP Tree Construction for Polygons • Split along the plane containing any polygon • Classify all polygons into positive or negative half-space of the plane • If a polygon intersects plane, split it into two • Recurse down the negative half-space • Recurse down the positive half-space

  12. Recap: BSP Tree Traversal for Polygons • Query: given a viewpoint, produce an ordered list of (possibly split) polygons from back to front: BSPnode::Draw(Vec3 viewpt) Classify viewpt: in + or - half-space of node->plane? // Call that the “near” half-space farchild->draw(viewpt); render node->polygon; // always on node->plane nearchild->draw(viewpt); • Intuitively: at each partition, draw the stuff on the farther side, then the polygon on the partition, then the stuff on the nearer side

  13. BSP Demo • Nice demo: • http://symbolcraft.com/graphics/bsp/index.html • Also has a link to the BSP Tree FAQ

  14. Ouch Summary: BSP Trees • Pros: • Simple, elegant scheme • Only writes to framebuffer (i.e., painters algorithm) • Thus once very popular for video games (but no longer, at least on PC platform) • Still very useful for other reasons (more later) • Cons: • Computationally intense preprocess stage restricts algorithm to static scenes • Worst-case time to construct tree: O(n3) • Splitting increases polygon count • Again, O(n3) worst case

  15. Warnock’s Algorithm (1969) • Elegant scheme based on a powerful general approach common in graphics: if the situation is too complex, subdivide • Start with a root viewport and a list of all primitives • Then recursively: • Clip objects to viewport • If number of objects incident to viewport is zero or one, visibility is trivial • Otherwise, subdivide into smaller viewports, distribute primitives among them, and recurse

  16. Warnock’s Algorithm • What is the terminating condition? • How to determine the correct visible surface in this case?

  17. Warnock’s Algorithm • Pros: • Very elegant scheme • Extends to any primitive type • Cons: • Hard to embed hierarchical schemes in hardware • Complex scenes usually have small polygons and high depth complexity • Thus most screen regions come down to the single-pixel case

  18. The Z-Buffer Algorithm • Both BSP trees and Warnock’s algorithm were proposed when memory was expensive • Ed Catmull (mid-70s) proposed a radical new approach called the z-buffer • (He went on to help found a little company named Pixar) • The big idea: resolve visibility independently at each pixel

  19. The Z-Buffer Algorithm • We know how to rasterize polygons into an image discretized into pixels:

  20. The Z-Buffer Algorithm • What happens if multiple primitives occupy the same pixel on the screen? Which is allowed to paint the pixel?

  21. The Z-Buffer Algorithm • Idea: retain depth (Z in eye coordinates) through projection transform • Recall canonical viewing volumes • Can transform canonical perspective volume into canonical parallel volume with:

  22. The Z-Buffer Algorithm • Augment framebuffer with Z-buffer or depth buffer which stores Z value at each pixel • At frame beginning initialize all pixel depths to  • When rasterizing, interpolate depth (Z) across polygon and store in pixel of Z-buffer • Suppress writing to a pixel if its Z value is more distant than the Z value already stored there • “More distant”: greater than or less than, depending

  23. Interpolating Z • Edge equations: Z is just another planar parameter: z = Ax + By + C • Look familiar? • Total cost: • 1 more parameter to increment in inner loop • 3x3 matrix multiply for setup • See interpolating color discussion from lecture 10 • Edge walking: can interpolate Z along edges and across spans

  24. The Z-Buffer Algorithm • How much memory does the Z-buffer use? • Does the image rendered depend on the drawing order? • Does the time to render the image depend on the drawing order? • How much of the pipeline do occluded polygons traverse? • What does this imply for the front of the pipeline? • How does Z-buffer load scale with visible polygons? With framebuffer resolution?

  25. Z-Buffer Pros • Simple!!! • Easy to implement in hardware • Polygons can be processed in arbitrary order • Easily handles polygon interpenetration • Enablesdeferred shading • Rasterize shading parameters (e.g., surface normal) and only shade final visible fragments • When does this help?

  26. Z-Buffer Cons • Lots of memory (e.g. 1280x1024x32 bits) • Read-Modify-Write in inner loop requires fast memory • Hard to do analytic antialiasing • Hard to simulate translucent polygons • Precision issues (scintillating, worse with perspective projection)

  27. Visibility Culling • The basic idea: don’t render what can’t be seen • Off-screen: view-frustum culling • Occluded by other objects: occlusion culling

  28. Motivation • The obvious question: why bother? • Off-screen geometry: solved by clipping • Occluded geometry: solved by Z-buffer • The (obvious) answer: efficiency • Clipping and Z-buffering take time linear to the number of primitives

  29. The Goal • Our goal: quickly eliminate large portions of the scene which will not be visible in the final image • Not the exact visibility solution, but a quick-and-dirty conservative estimate of which primitives might be visible • Z-buffer& clip this for the exact solution • This conservative estimate is called the potentially visible set or PVS

  30. Visibility Culling • The remainder of this talk will cover: • View-frustum culling (briefly) • Occlusion culling in architectural environments • General occlusion culling

  31. View-Frustum Culling • An old idea (Clark 76): • Organize primitives into clumps • Before rendering the primitives in a clump, test a bounding volume against the view frustum • If the clump is entirely outside the view frustum, don’t render any of the primitives • If the clump intersects the view frustum, add to PVS and render normally

  32. Efficient View-Frustum Culling • How big should the clumps be? • Choose minimum size so:cost testing bounding volume << cost clipping primitives • Organize clumps into a hierarchy of bounding volumes for more efficient testing • If a clump is entirely outside or entirely inside view frustum, no need to test its children

  33. Efficient View-Frustum Culling • What shape should the bounding volumes be? • Spheres and axis-aligned bounding boxes: simple to calculate, cheap to test • Oriented bounding boxesconverge asymptotically faster in theory • Lots of other volumes have been proposed, but most people still use spheres or AABBs.

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