Photorealistic%20Animation%20Rendering%20with%20Energy%20Redistribution

1
Photorealistic Animation Rendering with Energy
Redistribution

• Yu-Chi Lai ???
• University of Wisconsin - Madison

2
Agenda

• Introduction
• Physically-based rendering methods
• Population Monte Carlo energy redistribution
• Future works

3
Goal and Applications

• Goal generate realistic animations
• Applications
• Movie
• Interactive entertainments
• Computer games
• Virtual reality walk-throughs
• Light Engineering
• Etc.

From Day After Tomorrow
4
Applications
Animation Kristensen et al.
Grand Theft Auto 4
IGNEntertainment
5
Modeling and Simulating Appearance
6
Agenda

• Introduction
• Background
• Population Monte Carlo energy redistribution
• Future works

7
Rendering Equation

• Reflection Equation
• Energy Balance Equation
• Difficulty Lr appear in both sides of equation
  gt Fredholm equation of the second type

Incoming light
Sum
BRDF
Light reflected
incoming light reflected at the point
8
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.
9
Path Integral for General Integration

• Measurement equation
• Path Integral

• a path
• O path space
• area product measurement
• contribution of a path

• Difficulty high dimensions, computation grow
  exponentially when using deterministic
  integrations

10
Monte Carlo Algorithms

• We can estimate the integral by generating a set
  of samples
• Different ways to generate samples path tracing,
  light tracing, bidirectional,

11
Issues with MC methods

• Computationally expensive
• Variance reduced slowly with number of samples
• Reuse path samples

From PBRT Book
12
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
13
Physically-based Animation Rendering

• Right now the research is mainly from Germans
  MPI, USAs UCSD, Standford, and Cornell.
• Parallel independently rendering gt temporal
  coherence
• Use multiple processors to do independent ray
  tracing Warld01
• Coherently trace rays Kdtree, Grids, and
  bounding volume hierarchy (BVH) Wald01b,
  Wald07a
• Efficient update schemes of acceleration
  structure Popov06, Lauterbach06, Yoon07
• Implement global illumination in GPU architecture
  including radiosity, photonmapping, ray tracing,
  Purrel02, Purell03
• Copy the samples across the frames gt validity
• Irradiance Reuse.Martin99, Tawara02,
  Tawara04, Smyk05
• Photon shooting (next slide)

14
Photon Shooting

• Photon shooting algorithm Myszkowski01,
  Dmitriev02, Weber04
• Instant Radiosity Keller97, Wald02a, Laine07
• Light cut algorithm Walter05, Hansan07,
  Hansan08
• 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
15
Reuse Path Samples

• Camera is allowed to move Briere96,
  Murakami89, Jevans92, Sequin89, Bala99,
  Fernandez00, Havran03, Mendez06
• Light source is allowed to move or change
  properties Sbert04a, Sbert04b , Sbert04C,
  Ghosh06

Animation by Havran et al
Animation by Ghosh et al
16
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.

17
Agenda

• Introduction
• Background
• Population Monte Carlo energy redistribution
• Future works

18
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?

19
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

20
Metropolis and Energy Redistribution Path Tracing

• Generate a sequence of paths
  
• where path is generated according to

21
Overview of Population Monte Carlo Energy
Redistribution Animation Rendering System
22
PMC-ER in Each Frame Process
23
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

24
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

25
Population Monte Carlo Algorithm
To estimate integral At t iterations, a PMC
estimator of the integral is given by
26
(No Transcript)
27
Kernel Function and Adaptation

• Kernel Function
• Adapt 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

28
Adaptation Results

• Color represents perturbation radius
• Red 5, Green 10, Blue 50

29
Cornell Box
ERPT
PMC-ER
30
Room Scene
ERPT
PMC-ER
31
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
32
Regeneration (I)

• Perceptually distributed pixel positions
  according to which is the
  radiance sample variance in each pixel
• Weighting

33
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

34
Results
4SPPsReg
4SPPs
8SPPs
35
Results
6SPPsReg
6SPPs
12SPPs
18SPPs
36
Problem in Frame-by-Frame Rendering

• Each frame takes long time.
• Parallel rendering with condor system
• Temporal artifacts temporal perturbation

37
Temporal Perturbation

• Update the position of diffuse vertices
• Reconstruct the specular sub-path
• Check the validity of the path

38
Cornell Box
Frame-By-Frame
With Temporal Perturbation
39
Chess Body
Frame-By-Frame
With Temporal Perturbation
40
Room Scene
Frame-By-Frame
With Temporal Perturbation
41
Chess Board
Frame-By-Frame
With Temporal Perturbation
42
Basement
Frame-By-Frame
With Temporal Perturbation
43
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

44
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

45
Agenda

• Introduction
• Background
• Population Monte Carlo Energy Redistribution
• Future Works

46
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

47
Future Works

• Apply Population Monte Carlo with path tracing
  into animation rendering using environment map
  lighting.
• A path has the form of L(DS)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.

48
Future Research

• Explore the parallel ability in GPU
• Energy redistribution path tracing are naturally
  parallel. gt 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.

49
Publications

• Computer Science
• Yu-Chi Lai, Steven Chenney, Shaohua Fan Group
  Motion Graphs, Eurographics/SIGGRAPH Symposium
  on Computer Animation 2005, pp. 281290.
• 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)

50
Publications

• Computer Science (Others)
• Shaohua Fan, Stephen Chenney and Yu-Chi Lai
  Metropolis Photon Sampling With Optical User
  Guidance, Eurographics Symposium on Rendering,
  2005, pp. 127-138
• Yu-Chi Lai, Stephen Chenney, Shaohua Fan,
  Data-Driven Group Animation, Technical Report,
  Department of Computer Sciences, University of
  Wisconsin-Madison, 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

51
Publications

• Electrical and Computer Engineering
• 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)

52
Publications

• Chapters in books
• 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

53
Work Research Experience

• Research associate, Department of Electrical
  Engineering, National Cheng-Kong (1998 2000)
• Lead a group to write a program of satellite
  orbit simulation, and also participating in
  coding the drivers for CD-ROM and DVD, and GPSs
  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)

54
Thank YouQuestion?More Details
www.cs.wisc.edu/yu-chi
55
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73
Spatial Perturbation

• Perturbed the pixel position and reconstruct the
  lens edge
• Reconstruct the specular sub-paths
• Connect to the rest of paths.

74
Temporal Perturbation

• Update the position of diffuse vertices
• Reconstruct the specular sub-path
• Check the validity of the path

75
Photon Mapping

• Two pass light and eye pass
• Light pass shoots out photons to create photon
  maps
• Eye pass collects the radiance by splitting
• Ldirect CSL ( direct lighting algorithms)
• Lcaustics CSDSL (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

76
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, pre-computed
  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.

77
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?

78
Hybrid Algorithms

• Based on instant radiosityLaine07
• 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 Gautron05
• 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.
79
Physically-based Animation Rendering

• Right now the research is mainly from Germans
  MPI, USAs UCSD, Standford, and Cornell.
• Image-based global illumination gt hard for
  dynamic scene Nimeroff96, Myszkowski99
• Radiosity methods gt simple objects and material
• Progressive algorithms Chen90,George90,
  Muller95
• Hierarchical algorithmsForsyth94,Shaw97,
  Drettakis97, Martin99, Damez99
• Decouple render and display gt not really solve
  global illumination problem Walter99,
  walter02, Larson98, Ward99, Stamminger00,
  Simmons00, Tole02