Transcript Fast Scene Voxelization and its Applications Elmar Eisemann and Xavier Décoret i3D

i3D
Fast Scene Voxelization
and its Applications
Elmar Eisemann and Xavier Décoret
ARTIS-GRAVIR/IMAG-INRIA
ARTIS is a team of the GRAVIR/IMAG laboratory, a joint effort of CNRS, INRIA, INPG and UJF
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A long time ago ...
• Simple games and simple pleasures...
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Nowadays ...
• 3D
• Complex models
• Complex effects
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Context
• Complex and dynamic scenes
Need for
• Fast information acquisition
• Fast information evaluation
• Shader compatibility
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Context
• Lots of effects
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Context
• Lots of effects
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Context
• Lots of effects
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What is common?
• All use information from voxels!
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What is a Voxel?
• Space discretized by cubes (voxels)
• Can contain information
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What‘s good about voxels?
• Constant complexity
– (scene independent)
• Simple structure
• Simple entities
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What‘s bad about voxels?
• Storage cost (3D)
• Not GPU adapted
• Slow on CPU
100K polygons
octree 256 x 256 x 256
3 minutes [Haumont and Warzee 2002]
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Previous Work on GPU Voxelization
• Everitt et al. 2001 using Depth Peeling
– Layers are peeled off using zBuffers
• Pro:
– Representation is accurate from the viewpoint
• Contra:
– One pass per depth complexity
– Result not easy to use (and several textures)
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Goals of our approach
• Representation easy to use on GPU
• Result in one pass
• Handle depth complexity problem
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Previous Work on GPU Voxelization
• Dong, Chen, Bao, Zhang and Peng
Pacific Graphics 2004,
Real-time Voxelization for Complex Models
• Same key idea for representation
• Comparison later...
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Our contribution(s)
• Simple and compact representation
• GPU adapted (especially in future)
• Very fast
1.000 K polygons
1024 x 1024 x 128
At approx. 70Hz (~0.02 seconds)
• Three sample applications
Comes with a
price ...
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The price of speed
• Less information
– basically: 1 bit
– trade-off: grid resolution <> information
• Not accurate
– not watertight
For most applications this is not problematic
• Not hierarchical
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Let‘s voxelize ...
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Principle - The key idea
• Represent a 3D grid as a 2D image
slicemap
• Use GPU to fill grid by rasterizing
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Principle - Voxel encoding
• Associate bitmask to distance of fragment
2
1
8
4
32 128 2
16 64
1
8
4
1 bit = 1 slice
32 128 2
16 64
1
8
4
32 128
16 64
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Principle - Voxel encoding
• Fragments are ORed using OpenGL LogicOps
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Principle - Voxel encoding
• Shader extremely simple (<10 instructions)
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Principle - Voxel encoding
• 32 slices for 4 channels (RGBA) with 8 bits
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Principle - Voxel encoding
• How can we do better?
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Technical details - Precision
• Using MRT 4*32 = 128 in a single pass
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Principle - Grid
• Orthographic projection leads to a voxel cube
• Depth function can be modified
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Technical details – Local precision
useless voxels
uniform
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Technical details – Local precision
• Tighter interval using two depth maps:
less / greater depth test
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Technical details – Local precision
Less unused voxels
local
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Technical details – Local precision
• Very efficient:
– 1 or 2 depth renderings (FastZBuffer)
– still simple shader (2 supplementary texlookups)
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Limitations
Occur less due to high
image resolution
Well known problems...
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Limitations
• Max resolution 4096 x 4096 x 128
• Only rasterizable objects
• Different representation along Z-axis
– but can be beneficial
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Comparison to Dong et al.
• Same encoding in bits
• 3 slicemaps to solve “hole“ problem
– limits resolution or several render passes
– needs fusion into final voxel texture
• No local precision
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Applications
• Transmittance shadow maps
• Refraction
• Shadow volume culling and clamping
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Transmittance Shadow Maps - TSM
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TSM - Related Works
• Deep shadow maps [Lokovic and Veach 00]
• Opacity maps [Kim and Neumann 01]
• Nalu [Nguyen and Donnelly 05]
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TSM - Related Works
• Deep shadow maps [Lokovic and Veach 00]
• Opacity maps [Kim and Neumann 01]
• Nalu [Nguyen and Donnelly 05]
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Deep shadow maps
• Shadows for complex scenes
• 1D attenuation function per pixel
• Evaluation like shadow map
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Deep shadow maps
Pro:
Images courtesy of Lokovich and Veach, Deep Shadow Maps, Proc. of Siggraph 2000
• nice results
Contra:
• far from real-time
• no physical meaning
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TSM - Related Works
• Opacity maps [Kim and Neumann 01]
– Store float opacity in layers (interpolation simple)
– Creation of one layer uses whole geometry
– For GPU evaluation (original algo used CPU evaluation):
• Currently >16 layers possible perfomance drop[Koster04]
– Expensive for complex scenes and several layers
• Nalu [Nguyen and Donnelly 05]
– Close to opacity maps
– Store opacity in color channels
– Using MRT: 16 layers
Image copyright NVIDIA cooperation
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Transmittance shadow maps – Key idea
• Semi-transparent surfaces:
Attenuation =
nb of intersected surfaces
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Transmittance shadow maps – Key idea
• Transparent objects‘ slicemap
Attenuation =
nb of intersected voxels
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Transmittance shadow maps - Algo
• Input: Object with semi-transparent material
• 2 render passes:
– Light
– Viewer
163.000 tris
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Transmittance shadow maps - Algo
• Near/far depth maps of semi-transparent
parts and local slicemap
depth maps
slicemap
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Transmittance shadow maps - Shader
• Slicemap texlookup gives voxel column
slicemap
S(p)
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Transmittance shadow maps - Shader
• Value truncation by position
just a mod
S(p)
Z(p)
V(p)
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Transmittance shadow maps - Shader
• Bit count
tex lookup
bit count texture
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Transmittance shadow maps
Results:
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Transmittance shadow maps
• Trade-off: Precision vs. information
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Deep shadow maps in real time
• 3 phenomena:
partial occlusion
semi-transparent
volumetric
(small occluders)
(glass)
(fog)
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Deep shadow maps in real time
• 3 phenomena:
supersampling
partial occlusion
semi-transparent
volumetric
(small occluders)
(glass)
(fog)
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Deep shadow maps in real time
• 3 phenomena:
supersampling
TSM
partial occlusion
semi-transparent
volumetric
(small occluders)
(glass)
(fog)
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Deep shadow maps in real time
• 3 phenomena:
supersampling
TSM
Now...
partial occlusion
semi-transparent
volumetric
(small occluders)
(glass)
(fog)
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Applications
• Transmittance shadow maps
• Refraction
• Shadow volume culling and clamping
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Volumetric effects – Related Works
• Inspired by [Wyman 05]:
Refract ray twice:
front face normals and back face normals
Traversed depth approximated:
precalculation + depth map difference
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Volumetric effects – Approach
• Use volume info for refraction / scattering
as well as attenuation
Lokovic and Veach
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Volumetric effects - Algorithm
• Suppose: closed object
• Goal: traversed volume/create filled voxels
N
V
V R
R
V N N
V N N
V
Depth map difference works
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Volumetric effects - Algorithm
• Suppose: closed object
• Goal: traversed volume/create filled voxels
N
V
V R
R
V N N
V N N
V
Depth map difference fails
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Volumetric effects – Naive approach
• Single slicemap from eye and flood fill
N
V
V R
R
V N N
V N N
V
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Volumetric effects – Naive approach
• Single slicemap from eye and flood fill
• Problems:
– On GPU flood fill is too slow
– Evaluation texture is impossible
• More than 4 Gbyte for 32 slices
– Several faces in one voxel (ambiguity)
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Volumetric effects – Key Idea
• Create two slicemaps
• Front and back facing surfaces
N
V
V R
R
V N N
V N N
V
• This can be done in a single pass (MRT)
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Volumetric effects – Key Idea
• Two slicemaps allow incremental volume
computation via in/out states
N
V
V R
R
V N N
V N N
V
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Volumetric effects – Evaluation
• Evaluation texture for a single channel
– info to resolve ambiguity
• Texture lookups are independent
Details in paper
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Volumetric effects
Results:
>200 fps on a Geforce6800
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Applications
• Transmittance shadow maps
• Refraction
• Shadow volume culling and clamping
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Shadow volume culling and clamping
• CC ShadowVolumes
[Lloyd, Wendt, Govindaraju, Manocha 2004]
– Culling and Clamping of SV [Crow 77]
• CC Shadow volumes
• Caster culling:
+1
+1
-1
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CC Shadow volumes
• Shadow volume clampingReceiver culling:
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Shadow volume culling and clamping
• Our approach uses the slicemap to perform
shadow clamping (modified depth function)
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Shadow volume culling and clamping
• Our approach uses the slicemap to perform
shadow clamping (modified depth function)
Shadow volumes
CC shadow volumes
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Shadow volume culling and clamping
• Slicemap with modified depth function:
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Shadow volume culling and clamping
How to determine volume extent:
• Currently in a shader, 1 pass for 1 slice
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Shadow volume culling and clamping
Proposed hardware extension:
• OR in area of occluder would be sufficient
(1 pass for 128 slices)
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Shadow volume culling and clamping
• Slight Optimizations to improve culling and
clamping
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Conclusion
• Fast voxelization of highly complex scenes
• Grid of high resolution: 4096 x 4096 x 128
• Completely GPU based
• Input of almost arbitrary nature/topology
• Several applications possible
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And the future ...?
• 32 bit framebuffers imply 512 slices in 1 pass
• Direct X 10 implies bit operations
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Thank you very much
for your attention!