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Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Graphics Topics in VR By Shaun Nirenstein.

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Presentation on theme: "Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Graphics Topics in VR By Shaun Nirenstein."— Presentation transcript:

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2 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Graphics Topics in VR By Shaun Nirenstein

3 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Overview Impact of graphics/geometric algorithms on VR Visibility in VR Rendering Topics in VR Collision Detection Animation (I won’t talk about this)

4 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Impact of graphics/geometric algorithms on VR Constrains the VR Visibility Scene complexity Performance Shadows Cues Soft shadows offer more information about the light source Shadows are difficult(slow), soft shadows are more difficult(slow)

5 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Impact of graphics/geometric algorithms on VR Constrains the VR (cont.) Illumination models Defines the set of surface materials available Global vs. local illumination What can be done at real-time? –Global specular? –Global diffuse? –Arbitrary BRDF (Bidirectional Reflectance Distribution Function)? Collision detection How accurate? How fast? (Agent/Avatar) Animation Scripted, captured, simulated

6 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Visibility Obvious application is to manage geometric complexity Don’t render what you cannot see Less obvious application is to manage global complexity Don’t “simulate” invisible objects Can X see Y (e.g. AI) Don’t illuminate invisible objects Predictive cache management!!! Could Y be visible from X soon –Invisible geometry, textures, bump maps, vertex/pixel programs do not have to be resident

7 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Visibility Algorithms From-point techniques: What is visible from view point X From-region techniques: What is visible from view region R I.e. Y is visible from R, if there exists a point P in R, which can see Y Can bind a visible set to time

8 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town From Point Visibility Occluder shadow volumes Invisible Occluder

9 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Occluder Fusion (from point) Occluder shadow volumes Invisible Occluder Invisible Invisible???

10 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Occluder Fusion (from point) Cells and portals

11 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Occluder Fusion (from point) Cells and portals

12 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Occluder Fusion (from point) Cells and portals

13 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Problems Cells and portals Only work (well) for “architectural scenes” Occluder Shadows Fusion is difficult Only works well for a small number of occluders Other techniques offer various improvements and trade-offs Hierarchical Occlusion Maps Occlusion bit testing Hierarchical Z-Buffer Many more…

14 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town From Region Visibility Occluder shadow volumes Invisible Occluder

15 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town From Region Visibility Area light source analogy Separating lines Supporting lines Umbra Penumbra

16 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town From Region Visibility Area light source analogy Umbra?

17 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Occluder Fusion (from region) Cells and portals

18 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Occluder Fusion (from region) Cells and portals

19 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Occluder Fusion (from region) Cells and portals (visible volume)

20 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Occluder Fusion (from region) Cells and portals (visible volume)

21 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Occluder Fusion (from region) Cells and portals (visible cell iff. stabbing line does exist)

22 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Finding a stabber (2D) Find a line which separates two set of points

23 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Finding a stabber (2D) Find a line which separates two set of points Left and right sets (defined by orientation)

24 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Finding a stabber (2D) Find a line which separates two set of points Left and right sets (defined by orientation)

25 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Finding a stabber (2D) Find a line which separates two set of points Left and right sets (defined by orientation) Solved using duality

26 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Finding a stabber (3D) Also solved with duality Lines in 3D go to points in 5D Pluecker coordinates

27 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Constructing Cells/Portals BSP Tree – Splits volume until leaves are convex Portals are sides of leaf nodes which do not correspond to scene polygons

28 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Constructing Cells/Portals Optimal portal finding is an open problem Portals / Cells (sectors) are usually defined by hand

29 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Soft and Hard Shadows Hard Shadows – small (points) or far Soft Shadows – area/volume light source HardSoft

30 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Soft and Hard Shadows Soft shadows != Blurring!!! Light Occluder Ground

31 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Soft and Hard Shadows Algorithms Point sources are easy! Clip shadow volume against scene Ray tracing Shadow map Shadow volume Soft shadows are difficult! Soft shadow volumes Point sampling of area light source Ray tracing Hard and soft shadows may be pre-computed by sampling surface geometry and applying lightmaps

32 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Lightmaps Can be used for shadows, lighting, diffuse illumination Need to be recomputed when geometry and/or lights move * =

33 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Global vs. Local Illumination Global looks better – local is faster Trade offs between complexity, performance, ability to move geometry, quality, etc. What do games do? Radiosity preprocess into light maps Light grid for dynamic objects Bump mapping is applied in addition Many passes: textures, bumps, lightmaps, shadow passes, etc. Doom III? No global illumination Not necessary for the “feel” of the game Allows for dynamic hard shadows (cast BY everything ONTO everything) Photo-realism does not add as much to mood as shadows in this context

34 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Photon Mapping

35 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Photon Mapping

36 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Photon Mapping

37 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection Why? Need to know if movement results in solid bodies colliding Physics Visibility

38 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection Broad Phase Conservative – only test whether or not further testing(narrow phase) is required Uses bounding volumes and bounding hierarchies

39 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection Narrow Phase Accurate Triangle-triangle intersection Segment-triangle intersection Bounding-volume triangle intersection

40 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection(cont.) What makes a good bounding box? Easy to test for collision Tightly represents the model – minimal extraneous volume More information implies better potential What about moving objects? On the fly creation? Conservative updates Tracking nearest geometry

41 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection(cont.) AABB (Axially aligned bounding boxes) Two points in 3D (6 scalars) BS (Bounding Sphere ) Point and radius (4 scalars) Not always a good fit – may require OBB (Oriented bounding box) Three points in 3D (9 scalars ) Principal component analysis

42 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection(cont.) Convex Hull Accurate Conservative bounding planes faster, but less accurate

43 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection(cont.) k-dops (discrete oriented polytopes) Accurate – more planes AABB == 6-dop

44 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection(cont.) 8-dop 45 o

45 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection(cont.) Hierarchies – AABB Test top down

46 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection(cont.) Hierarchies – OBBTree Test top down

47 Collaborative Visual Computing Lab Department of Computer Science University of Cape Town Collision Detection(cont.) Polytope-polytope intersection (narrow phase) Assuming non-containment: Intersection is equivalent to the existence of an edge of one polytope which intersects the face of another Containment

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