Transcript Photorealistic Animation Rendering with Energy Redistribution Yu-Chi Lai 賴祐吉

Photorealistic Animation Rendering
with Energy Redistribution
Yu-Chi Lai 賴祐吉
University of Wisconsin - Madison
Yu-Chi Lai
Agenda
• Introduction
• Physically-based rendering methods
• Population Monte Carlo energy redistribution
• Future works
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Goal and Applications
• Goal: generate realistic
animations
• Applications
– Movie
– Interactive entertainments
• Computer games
• Virtual reality walk-throughs
– Light Engineering
– Etc.
From Day After Tomorrow
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Applications
Animation: Kristensen et al.
Grand Theft Auto 4
IGNEntertainment
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Modeling and Simulating Appearance
Human Perception
Scene Descritpion
- Lights
- Geometries
- Camera & Film
- Others
Rendering
- Lights: release the energy.
- Geometries: bounce the energy
- Camera & Film: absorb the
energy to generate images
Image Frames
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Agenda
• Introduction
• Background
• Population Monte Carlo energy redistribution
• Future works
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Rendering Equation
• Reflection Equation
Lr ( xt  xt )   f s ( x t  xt  xt ) Li ( x t  xt )
M
Light
reflected
Sum
Incoming light
BRDF
incoming light reflected at the point
• Energy Balance Equation
x
L( x  t  x  t )  Le ( x  t  x  t )  Lr ( x  t  x  t )
• Difficulty: Lr appear in both sides
of equation => Fredholm equation
of the second type
x
x
t
x  t
t
t
xt
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Physically-based Rendering
• Render images according to
physical principles
– Radiosity: finite element
– Ray-tracing: based on Monte Carlo
integrations
• Unbiased: path tracing, bidirectional
path tracing, metropolis light transport,
energy redistribution path tracing and
so on.
• Biased: irradiance caching, photon
mapping, and so on.
From Jenson et al.
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Path Integral for General Integration
• Measurement equation:
• Path Integral:
– X~ t : a path X~ t  x1t x2t  xnt
– Ω: path space
–
: area product measurement
–
: contribution of a path
•Difficulty: high dimensions, computation grow exponentially
when using deterministic integrations
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Monte Carlo Algorithms
• We can estimate the integral by generating a set of
samples: X~ T , X~ T ,, X~ T
0
0
1
1
N
N
• Different ways to generate samples: path tracing,
light tracing, bidirectional, …
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Issues with MC methods
• Computationally expensive
• Variance reduced slowly
with number of samples
var ~ 1 / N
• Reuse path samples
From PBRT Book
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Frame-by-Frame Photorealistic
Animation Rendering
• Takes a long time to generate
– Several hours per frame is
industry standard
• Temporal noise
– Flickering
– Shimmering
From Max-Planck Institute, German
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Physically-based Animation Rendering
• Right now the research is mainly from German’s MPI, USA’s
UCSD, Standford, and Cornell.
• Parallel independently rendering => temporal coherence
– Use multiple processors to do independent ray tracing [Warld’01]
– Coherently trace rays: Kdtree, Grids, and bounding volume hierarchy
(BVH) [Wald’01b, Wald’07a]
– Efficient update schemes of acceleration structure [Popov’06,
Lauterbach’06, Yoon’07]
– Implement global illumination in GPU architecture including radiosity,
photonmapping, ray tracing, …[Purrel’02, Purell’03]
• Copy the samples across the frames => validity
– Irradiance Reuse.[Martin’99, Tawara’02, Tawara’04, Smyk’05]
– Photon shooting (next slide)
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Photon Shooting
• Photon shooting algorithm [Myszkowski’01, Dmitriev’02, Weber’04]
• Instant Radiosity [Keller’97, Wald0’2a, Laine’07]
• Light cut algorithm: [Walter’05, Hansan’07, Hansan’08]
– Create a set of point light sources in the entire animation
– Cluster the light sources into a tree according to the perceptual metrics in temporal
and spatial domain
Animation by Hansan
et al
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Reuse Path Samples
• Camera is allowed to move [Briere’96,
Murakami’89, Jevans’92, Sequin’89,
Bala’99, Fernandez’00, Havran’03,
Mendez’06]
• Light source is allowed to move or
change properties: [Sbert’04a, Sbert’04b ,
Sbert’04C, Ghosh’06]
Animation by Havran
et al
Animation by Ghosh
et al
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Grand Challenge
• Efficiently render entire animation
–
–
–
–
Do parallel computation in multi-processors or GPU.
Do coherent ray tracing.
Efficiently update the acceleration structure.
Reuse samples from previous computation
• Reduce the temporal artifacts
– Explore the temporal coherence among paths
– Reuse the computation results.
• Perceptual evaluation of the rendering results.
– Evaluate the strength of each algorithm.
– Allow us to distribute computation to perceptual important
features.
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Agenda
• Introduction
• Background
• Population Monte Carlo energy redistribution
• Future works
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Challenges
• How to adjust the sampling parameter according to
path or scene properties?
• How to concentrate more computation on paths that
are important without introducing bias?
• How to reuse paths temporally?
• How to handle the huge computation for animation
rendering?
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Markov Chain Monte Carlo
• Write the integrand as:
–
–
–
: the sensor measurement for pixel j of frame k
: represents all other factors
: represents the radiant energy passing
through the image sweep
– Create the distribution of paths
in animation proportional to the
contribution
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Metropolis and Energy
Redistribution Path Tracing
• Generate a sequence of paths:
where path
is generated according to
ERPT
MLT
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Overview of Population Monte
Carlo Energy Redistribution
Animation Rendering System
Daemon
Preprocessing
Create Script for
Each Frame
Collect Data
Update Iteration
Information
Condor Pool
Frame
Process
Frame
Process
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PMC-ER in Each Frame Process
Preprocess
Energy
Redistribution
Resampling
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Detail
• Preprocess: collect the information for the following
computation
• Energy redistribution: distribute the energy to similar paths
by using spatial and temporal perturbations.
• Resampling:
– Eliminate paths from the population.
– Generate replaced paths to determine the area of exploration.
– Adjust the rendering parameters
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Adjust Sampling Parameters (EGSR07)
• Different regions have
different details
• We would like to adjust
sampling parameters
accordingly
– Low detailed regions: large
distribution radius
– High detailed regions:
smaller distribution radius
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Population Monte Carlo Algorithm
Time t -1
To estimate integral
At t iterations, a PMC
estimator of the integral is
given by
Time t
p1t1,t-1
X
X 1,t
p1t
X
1,t
X2,t-1
X 2,t
X2,t
X3,t-1
X 3,t
X3,t
.
.
.
.
.
.
.
.
.
p1t
Kernel
Sampling
K i ,t 1 ( xt | X t 1 )
ReSampling
based on weghts
Wit   ( X 'it ) / K i ,t 1 ( X 'it | X t 1 )
Adjust K i ,t 1 ( x) based on X i ,t
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Kernel Function and Adaptation
• Kernel Function
• Adapt  ' s values: to choose proper perturbation radius
– Initialize them to constant values when a path is generated
– After each successful perturbation, the acceptability is labeled with
the perturbation radius, and the path, i
– By using
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Adaptation Results
• Color represents perturbation radius
– Red: 5, Green: 10, Blue: 50
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Cornell Box
PMC-ER
ERPT
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Room Scene
PMC-ER
ERPT
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Concentrate More Computation on
Certain areas (ISVC)
• Stratified exploration of the image plane
– The importance of regions on the image are not
perceptually the same.
– Some types of paths are visually more important and
harder to find.
PMC-ER 4SPPs
PMC-ER 8SPPs
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Regeneration (I)
• Perceptually distributed
pixel positions according
to
which
is the radiance sample
variance in each pixel
• Weighting
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Regeneration (II)
• Use light tracing to generate a
valid light paths
• Link each surface vertex to
the camera to form a set of
valid paths
• Evaluate whether it is a
caustics path
• Weighting
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Results
4SPPs+Reg
4SPPs
8SPPs
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Results
6SPPs+Reg
6SPPs
12SPPs
18SPPs
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Problem in Frame-by-Frame
Rendering
• Each frame takes long time.
– Parallel rendering with condor
system
• Temporal artifacts: temporal
perturbation
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Temporal Perturbation
• Update the position of diffuse
vertices
• Reconstruct the specular sub-path
• Check the validity of the path
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Cornell Box
Frame-By-Frame
With Temporal Perturbation
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Chess Body
Frame-By-Frame
With Temporal Perturbation
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Room Scene
Frame-By-Frame
With Temporal Perturbation
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Chess Board
Frame-By-Frame
With Temporal Perturbation
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Basement
Frame-By-Frame
With Temporal Perturbation
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Contributions
• A new rendering algorithm based on PMC framework
•
•
•
•
– Correlatedly explore important paths
– Automatically adjust energy redistribution area according to the
information collected in previous iterations
– Elimination-regeneration to achieve ergocity and adjust the
exploring area according to paths’ remaining energy
New lens perturbation method
– Increase the caustics perturbation success rate
– Ease the control of caustics perturbation on the image plane
New regeneration methods
– Concentrate the computation on perceptual important regions
– Concentrate the computation on perceptual important types of paths.
Temporal perturbation method: exploration the temporal coherence
among paths
A algorithm allows us to render a scene in parallel
Yu-Chi Lai
Limitations
• Human observation is the evaluation tool for animation quality.
• Dark regions are hard to get the chance to be explored and thus are
relatively noisy. Although it is hard to notice in single image, this
becomes an issues because human perception is very sensitive to this
kind of temporal inconsistency.
• Temporal perturbations in each condor process will create a large set of
temporal files for related frames. Transferring and updating data in
condor daemon process involves a large number of disk IOs.
• Our variance-sample distribution criterion is based on variance of
sample radiances but this did not represent the result after energy
redistribution.
• We separate perturbations into two types, temporal and spatial
perturbations, and this makes control harder and the initial probing
samples for each perturbation is relative low.
• Limit the light to area light sources and the efficiency goes down when
the number of lights goes up
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Agenda
• Introduction
• Background
• Population Monte Carlo Energy Redistribution
• Future Works
Yu-Chi Lai
Future Works
• Animation quality evaluation algorithms
– Current available perceptual animation quality evaluation
algorithm is for video compression.
– Adjust the quality perceptual evaluation algorithm for
Monte Carlo algorithms
• Construct a temporal filter based on result of the
temporal perturbations:
– The result of temporal perturbation can create the relations
among pixels in different frames, if we can use this relation
information to create a temporal filter accordingly, we
should be able to reduce the temporal artifact and iterations
to generate a smooth result
• Develop an perturbation which perturb in spatial
domain randomly but perturb in a fixed regions in
temporal domain deterministically
Yu-Chi Lai
Future Works
• Apply Population Monte Carlo with path tracing into
animation rendering using environment map lighting.
– A path has the form of L(D|S)C.
– For each path of current frame, temporally trace the path
with a proper temporal perturbation algorithm to enhance
the temporal coherence among frames.
• Spread the photon collection positions in photon
splatting with Metropolis:
– Generate a set of collection positions
– Use temporal perturbation to correlatedly generate new
photon collection positions from the previous frame.
• Use the light cut or light clusters algorithm to solve
the many light problem.
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Future Research
• Explore the parallel ability in GPU
– Energy redistribution path tracing are naturally parallel. =>
transform the ERPT algorithms onto GPU
– Explore the research possibility in environment map lighting and
shadow generation.
• Construction and application of flock tiles:
– If we can find a common set of temporal and spatial boundary
conditions for setting up a tile.
– We can use the constraint simulation to simulate the inner agents’
motion according to flock rules
– The animation tiles can be used to construct a seamless animation
such as a large crowd in a city, a school of fishes, a flock of birds or
the traffics in a city.
Yu-Chi Lai
Publications
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Computer Science
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Yu-Chi Lai, Steven Chenney, Shaohua Fan “Group Motion
Graphs”, Eurographics/SIGGRAPH Symposium on Computer
Animation 2005, pp. 281–290.
Yu-Chi Lai, Shaohua Fan, Stephen Chenney, and Charles Dyer,
“Photorealistic Image Rendering with Population Monte Carlo
Energy Redistribution”, Eurographics Symposium on Rendering,
2007, pp. 287-296.
Yu-Chi Lai, Feng Liu, Li Zhang, and Charles Dyer, “Efficient
Schemes for Monte Carlo Markov Chain Algorithms in Global
Illumination”, Proc. 4th International Symposium on Visual
Computing, 2008.
Yu-Chi Lai, Feng Liu, and Charles Dyer, “Physically-based
Animation Rendering with Markov Chain Monte Carlo”, (submit
to Eurographics Symposium on Rendering 2009)
Yu-Chi Lai
Publications
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Computer Science (Others)
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Shaohua Fan, Stephen Chenney and Yu-Chi Lai “Metropolis Photon Sampling With
Optical User Guidance”, Eurographics Symposium on Rendering, 2005, pp. 127138
Yu-Chi Lai, Stephen Chenney, Shaohua Fan, “Data-Driven Group Animation”,
Technical Report, Department of Computer Sciences, University of WisconsinMadison, 2005
Yu-Chi Lai, Shaohua Fan, and Charles Dyer, “Population Monte Carlo Path
Tracing”, Technical Report, Department of Computer Sciences, University of
Wisconsin-Madison, 2006
Shaohua Fan, Stephen Chenney, Bo Hu, Kam-Wah Tsui and Yu-Chi Lai, “Optimum
Control Variate”, Computer Graphics Forum, Vol. 25, No. 3, pp. 351-358, 2006.
Yu-Chi Lai, Shaohua Fan, Feng Liu, Brandom Smith, Stephen Chenney, Li Zhang
and Charles Dyer, “Population Monte Carlo Sampler for Rendering”, Technical
Report, Department of Computer Sciences, University of Wisconsin-Madison,
2009
Yu-Chi Lai
Publications
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Electrical and Computer Engineering
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Lai, Y-C, D. Haemmerich, et al (2003). “Lesion Size estimator at
different common locations with different tip temperature during
cardiac radio-frequency ablation”, IEEE Transactions on
Biomedical Engineering.
Lai, Y-C et al (2009). “Guidelines for predicting lesion size at
different common locations with different temperature during in
vitro radio-frequency ablation”, (Prepare)
Lai, Y-C et al (2009). “The effects of insertion depth and meat
dimension on the lesion formation during cardiac radio-frequency
ablation”, (Prepare)
Yu-Chi Lai
Publications
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Chapters in books
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“Biomedical Electrode”: John Webster ed., Ch 8
Electrocardiogram
“Introduction to biometric identification”, Willians
Tompkin ed., Ch 12 Biometric standards, testing, and
evaluation
“Tissue ablation: devices and procedures”, John G.
Webster ed., Ch. 28. Lesion size estimator
Yu-Chi Lai
Work & Research Experience
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Research associate, Department of Electrical
Engineering, National Cheng-Kong (1998 – 2000)
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Lead a group to write a program of satellite orbit simulation,
and also participating in coding the drivers for CD-ROM and
DVD, and GPS’s map display system.
Research Assistant, Department of Electrical and
Computer Engineering, UW-Madison (2001 – 2004)
Research Assistant, Department of Computer Science,
UW-Madison (2005-2006)
Summer Internship, Raven Software (2007 summer)
Teaching Experience (1994 to 1996 in National Taiwan
University, 2003 – 2008 in UW-Madision)
Yu-Chi Lai
Thank You
Question?
More Details: www.cs.wisc.edu/~yu-chi
Yu-Chi Lai
Reference
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Yu-Chi Lai
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Yu-Chi Lai
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Yu-Chi Lai
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[Smky’05]: Smky, M.; Kinuwaki, S.-i.; Durikovic, R. & Myszkowski, K.:
Temporally Coherent Irradiance Caching for High Quality Animation Rendering,
The European Association for Computer Graphics 26th Annual Conference
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[Adelson’95]: Adelson, S. J. & Hodges, L. F.: Generating Exact Ray-Traced
Animation Frames by Reprojection, IEEE Comput. Graph. Appl., IEEE
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[Badt’88]: Jr., S. B.: Two algorithms for taking advantage of temporal coherence
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Yu-Chi Lai
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[Stamminger’00]: Stamminger, M.; Haber, J.; Schirmacher, H. & peter Seidel,
H.: Walkthroughs with corrective texturing, tal Signal Processing. California
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[Simmons’00]: Simmons, M. & Sequin, C. H.: Tapestry: A dynamic mesh-based
display representation for interactive rendering, Proceedings of the 11th
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[Tole’02]: Tole, P.; Pellacini, F.; Walter, B. & Greenberg, D. P.: Interactive
global illumination in dynamic scenes, SIGGRAPH '02: Proceedings of the 29th
Annual Conference on Computer Graphics and Interactive Techniques, ACM
Press, 2002, 537-546
[Mendez’06]: Mendez-Feliu, A.; Sbert, M. & kalo, L. S.: Reusing Frames in
Camera Animation, Journal of WSCG, 2006, 14
[Sbert’04a]: Sbert, M.; Szecsi, L. & Szirmay-Kalos, L.: Real-time Light
Animation, Computer Graphics Forum (Proceedings Eurographics 2004), 2004,
23(3), 291-300
Yu-Chi Lai
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[Sbert’04b]: Sbert, M. & Castro, F.: Reuse of Paths in Final Gathering Step with
Moving Light Sources, International Conference on Computational Science
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[Sbert’04c]: Sbert, M.; Castro, F. & Halton, J.: Reuse of Paths in Light Source
Animation, CGI '04: Proceedings of the Computer Graphics International,
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[Ghosh’06]: Ghosh, A.; Doucet, A. & Heidrich, W.: Sequential Sampling for
Dynamic Environment Map Illumination, Proc. Eurographics Symposium on
Rendering, 2006, 115-126
[Briere’96]: Briere, N. & Pierre, P.: Hierarchical view-dependent structures for
interactive scene manipulation, SIGGRAPH '96, 1996, 83-90
[Murakami’89]: Murakami, K. & Hirota, K.: Incremental ray tracing,
Eurographics Workshop on Photosimulation, Realism and Physics in Computer
Graphics, 1989
Yu-Chi Lai
Reference
• [Murakami’89]: Murakami, K. & Hirota, K.: Incremental ray tracing,
Eurographics Workshop on Photosimulation, Realism and Physics in
Computer Graphics, 1989
• [Jevans’92]: Jevans, D. A.: Object space temporal coherence for ray
tracing, Proceedings of the conference on Graphics interface '92,
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SIGGRAPH '89: Proceedings of the 16th annual conference on
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editing using ray segment trees,
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P.: Interactive Direct Lighting in Dynamic Scenes, 2000
Yu-Chi Lai
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[Muuss’95a]: Muuss, M. J.: Toward real-time ray-tracing of combnatorial solid geometric
models, Proceeding of BRL-CAD Symposium, 1995
[Muuss’95b]: Muuss, M. J. & Lorenzo, M.: High-resolution interactive multispectral
missile sensor simulation for atr and dis., Proceeding of BRL-CAD Symposium, 1995
[Parker’99a]: Parker, S.; Martin, W.; Livnat, Y.; Sloan, P.; Shirley, P.; Smits, B. & Hansen,
C.: Interactive Ray Tracing, Symposium on Interactive 3D Computer Graphics, 1999
[Parker’99b]: Parker, S.; Martin, W.; Livnat, Y.; Sloan, P.; Shirley, P.; Smits, B. & Hansen,
C.: Interactive Ray Tracing for volume visualization, IEEE transaction on COmputer
Graphics and Visualization, 1999, 5
[Wald’01a]: Wald, I.; Slusallek, P. & Benthin, C. S.J.Gortler & K.Myszkowski (ed.):
Interactive Distributed Ray Tracing of Highly Complex Models, Rendering Techniques
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[Wald’01b]: Wald, I.; Benthin, C.; Wagner, M. & Slusallek, P. Bhalmers, A. & Rhyne, T.M. (ed.):
Interactive Rendering with Coherent Ray Tracing, Computer Graphics Forum
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for Realtime Ray Tracing, Proceedings of ACM SIGGRAPH 2005, 2005, 434-444
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[Gribble’06]: Gribble, C.; Ize, T.; Kensler, A.; Wald, I. & Parke, S. G.: A Coherent Grid
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Yu-Chi Lai
Reference
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Yu-Chi Lai
Spatial Perturbation
• Perturbed the pixel position
and reconstruct the lens
edge
• Reconstruct the specular
sub-paths
• Connect to the rest of paths.
Yu-Chi Lai
Temporal Perturbation
• Update the position of
diffuse vertices
• Reconstruct the specular
sub-path
• Check the validity of the
path
Yu-Chi Lai
Photon Mapping
• Two pass: light and eye pass
– Light pass shoots out photons to create photon
maps
– Eye pass collects the radiance by splitting
Lr  Ldirect  Lindirect  Lcaustics
• Ldirect: CS*L ( direct lighting algorithms)
• Lcaustics: CS*D+S*L (caustics map)
• Lindirect: all others involve more than one diffuse
surfaces (global map or final gathering)
• Can generate good results but introduce bias
and final gathering is still very time
consuming
Yu-Chi Lai
Physically-based Animation Rendering
• Photon shooting algorithms
– Photon shooting
– Instant radiosity
– Light cut
• Path reusing algorithms
• GPU-based algorithms
– Two phase pre-computation rendering: separate the rendering
into two phases: preprocess computation (CPU) and real-time
rendering (GPU) such as environment map prefiltering, precomputed radiance transfer, relighting, …
– Hybrid methods: separate the algorithm into two parts: one is
computed by CPU and the other is by GPU to take advantage of
both such as instant radiosity, photon splatting, and its
extensions.
Yu-Chi Lai
Grand Challenge
• Efficiently render entire animation
–
–
–
–
Do parallel computation in multi-processors or GPU.
Do coherent ray tracing.
Efficiently update the acceleration structure.
Reuse samples from previous computation
• Reduce the temporal artifacts
– Exploration the temporal coherence among paths
– Reuse the computation results.
• Perceptual evaluation of the rendering results.
– Evaluate the strength of each algorithm.
– Allow us to distribute computation to perceptual important features.
• Challenge in two phase pre-computation methods
–
–
–
–
Efficiently generate accurate data
Efficiently store and retrieve the data
Handle the movement and change of objects and scenes
Can we compute the data on fly?
Yu-Chi Lai
Hybrid Algorithms
• Based on instant radiosity[Laine’07]:
View
– Create a set of virtual lights and then create a
set of shadow maps
– Use the depth in the shadow map to determine
the visibility of rendering points
• Based on photon splatting [Gautron’05]
Photon
maps
– Cpu generate a set of photon maps and then
translate the gpu
– GPU trace the collection and use the photon
maps to deposit energy on each collection
position
• Simplify the global illumination
Animation: Laine et al.
Yu-Chi Lai
Physically-based Animation Rendering
• Right now the research is mainly from German’s MPI,
USA’s UCSD, Standford, and Cornell.
• Image-based + global illumination => hard for dynamic
scene [Nimeroff’96, Myszkowski’99]
• Radiosity methods => simple objects and material
– Progressive algorithms [Chen’90,George’90, Muller’95]
– Hierarchical algorithms[Forsyth’94,Shaw’97, Drettakis’97,
Martin’99, Damez’99 ]
• Decouple render and display => not really solve global
illumination problem [Walter’99, walter’02, Larson’98,
Ward’99, Stamminger’00, Simmons’00, Tole’02]
Yu-Chi Lai