SlideShare uma empresa Scribd logo
1 de 26
Baixar para ler offline
KAIST Computer Science
Global illumination for
PIXAR® movie production
20100121
Jaehyun Jang
KAIST Computer Science
• Global illumination for movie production
• Current Lighting Computation Methods
• Point-based Global Illumination for Movie Production
• Physically-based Lighting at PIXAR
• Global illumination researches in PIXAR®
• Rendering Pipeline in Production (as a Rendering TD)
Contents
KAIST Computer Science
• The first 3D animation used global illumination - Shrek 2 (2004)
Global illumination for movie production
Fig 1. Shrek 2.
[Photograph]. Retrieved from http://www.awn.com/vfxworld/illuminating-global-illumination
Courtesy of Paramount Pictures.
KAIST Computer Science
• Faking it : adding extra light sources
labour intensive
• Ray Tracing : requires many rays + shader evaluations
Too much slow (at 2010!)
• Radiosity
Requires entire scene data on memory
• Point-based
Little memory, no shader evaluations
Current Lighting Computation Method
KAIST Computer Science
Current : Physically-based Ray Tracing
Fig 2. Monster University
[Photograph]. Retrieved from http://neogaf.com/forum/showthread.php?t=569821
Courtesy of Disney-PIXAR
• PIXAR has been rendering their movie using physically based ray-tracing after
Monster University (2013)
KAIST Computer Science
Past : Point-based Global Illumination Techniques
Fig 3. Toy Story 3
[Photograph]. Retrieved from http://graphics.pixar.com/library/PointBasedGlobalIlluminationForMovieProduction/
Courtesy of Disney-PIXAR
• PIXAR uses point-based global illumination for rendering at 2010. At that time, ray-
tracing cost is too high to render images.
KAIST Computer Science
• First introduced this technique in ‘Point-Based Approximate Color Bleeding’, (2008).
• Background : Ray-tracing based global illumination is still expensive.
• Advantages using point-based :
1. Fast Computation
2. Noisy-Free
• Disadvantages :
1.Multi-pass approach, it cannot guarantee results as precise as ray tracing.
Point-Based GI for Movie Production (2010)
KAIST Computer Science
Point-Based GI for Movie Production (2010)
• Point Cloud
Each point : position, normal, radius, color = a colored disk
Color : the direct illumination at that surface position
How to generate? : PRMan to tessellate the surfaces into small micropolygons,
compute direct illumination from all light sources by using surface shader.
—> This approach is “Baking the direct illumination” (TD Terminology)
KAIST Computer Science
Point-Based GI for Movie Production (2010)
• Compute octree
A bottom-up computation
Consisting a node similar normals
Compute a spherical harmonic from leaf-node
Leaf-node : the sums of the coefficients for the surfels in the node.
Non-leaf-node : the sums of the coefficients of its child nodes.
KAIST Computer Science
Point-Based GI for Movie Production (2010)
Fig 4. Rasterization onto six raster cube faces
[Photograph]. Retrieved from http://
graphics.pixar.com/library/
PointBasedGlobalIlluminationForMovieProducti
on/
Courtesy of Disney-PIXAR
• Compute diffuse, and glossy global illumination
Traverse octree, visiting a node and rasterize the
illumination from node.
Rasterize colors contributing to a point : world
“as seen” by that point (a low resolution fish-eye
image)
Convolution with the BRDF
1. loop over raster pixels and multiplying
colors with the BRDF for the direction
corresponding to that pixel.
2. Can deal with glossy global illumination
KAIST Computer Science
Point-Based GI for Movie Production (2010)
Fig 5. Rendering with PRMan, baked radiosity value of point cloud (700,000 points) (left), glossy reflection (right)
[Photograph]. Retrieved from http://penguin.ewu.edu/RenderMan/RMS_2.0/pointbased.html
Courtesy of Disney-PIXAR
KAIST Computer Science
Point-Based GI for Movie Production (2010)
• Variation and extensions
Area light sources and soft shadows
Environment illumination
Multiple diffuse bounces
Final gathering for photon mapping
Ambient occlusion and reflection occlusion
etc.
KAIST Computer Science
Point-Based GI for Movie Production (2010)
Fig 6. Textured and displaced area light sources
[Photograph]. Retrieved from http://penguin.ewu.edu/RenderMan/RMS_2.0/pointbased.html
Courtesy of Disney-PIXAR
KAIST Computer Science
Point-Based GI for Movie Production (2010)
Fig 7. Point cloud, Ambient occlusion, Reflection Occlusion, additional environment reflection
[Photograph]. Retrieved from http://penguin.ewu.edu/RenderMan/RMS_2.0/pointbased.html
Courtesy of Disney-PIXAR
KAIST Computer Science
• The lighting pipeline at PIXAR was completely rewritten
and switched to a physically based and ray-traced system.
• Rendering Equation
L : radiance, f : BRDF
2 parts working in tandem :
1.Physically correct lights emitting energy in the scene
2.Physically correct BRDFs bouncing energy in the
scene
Physically based rendering pipeline (2013)
KAIST Computer Science
• Break down the rendering equation, each part will be solved by different
coshaders(defined in RSL 2.0) called integrators (http://renderman.pixar.com/view/
coshaders)
•
!
!
• direct lighting integrator + indirect diffuse integrator + indirect specular integrator
Physically based rendering pipeline (2013)
KAIST Computer Science
Fig 8. Light reflection
[Photograph]. Retrieved from http://content.gpwiki.org/index.php/D3DBook:
(Lighting)_Foundation_and_theory
Courtesy of Wikimedia
KAIST Computer Science
• Direct Lighting Integrator (Coshader)
1.Sample from lobes using BRDF coshaders
2.Sample from lights using light coshaders
3.Combine samples using Multiple Importance Sampling (Ryusuke Villemin, et al.
2013).
Physically based rendering pipeline (2013)
KAIST Computer Science
Fig 9. Structures communicates data between three coshaders consisting of Direct Light Integrator
[Photograph]. Retrieved from http://graphics.pixar.com/library/PhysicallyBasedLighting/paper.pdf
Courtesy of Disney-PIXAR
KAIST Computer Science
Algorithm 1. (Light Integration)
Several algorithms in the paper : http://graphics.pixar.com/library/PhysicallyBasedLighting/paper.pdf
KAIST Computer Science
Fig 10. Various luminaries in this shot, The Blue Umbrella
[Photograph]. Retrieved from http://graphics.pixar.com/library/PhysicallyBasedLighting/paper.pdf
Courtesy of Disney-PIXAR
KAIST Computer Science
Fig 11. Physically-based lighting in Monster University
[Photograph]. Retrieved from http://blog.selfshadow.com/publications/s2013-shading-course/pixar/
s2013_pbs_pixar_slides.pdf
Courtesy of Disney-PIXAR
KAIST Computer Science
Fig 12. Physically-based lighting in Monster University
[Photograph]. Retrieved from http://blog.selfshadow.com/publications/s2013-shading-course/pixar/
s2013_pbs_pixar_slides.pdf
Courtesy of Disney-PIXAR
KAIST Computer Science
• Based on PIXAR online library (from 2011 - now)
• Sampling
Importance sampling
1. A statistical framework for comparing importance sampling methods, and an
application to rectangular lights (Leonid Pekelis, et al. 2014).
2. Multiple Importance Sampling for Emissive Effects (Ryusuke Villemin, et al.
2013).
3. Importance Sampling of Reflections from Hair Fibers (Christophe Hery, et al.
2011).
Stratified Sampling
1. Correlated Multi-Jittered Sampling (Andrew Kensler, 2013).
Global Illumination Researches in PIXAR
KAIST Computer Science
• Caching
1. Multiresolution Radiosity Caching for Efficient Preview and Final Quality
Global Illumination in Movies (Per H. Christensen, et al. 2012)
• Summary
PIXAR researches physically-based ray tracing, their rendering pipeline running on
monte-carlo ray tracing, and it needs to develop proper sampling techniques for
BRDF and etc.
Global Illumination Researches in PIXAR
KAIST Computer Science
• Physically-based rendering is production standard.
• Current PRMan® pipeline, RSL 2.0 supports physically plausible shaders.
• For rendering technical directors, these kind of techniques are tremendously
demanded.
• — All is commented by technical director in PIXAR.
Rendering Pipeline in Production

Mais conteúdo relacionado

Mais procurados

stduy Edge-Based Image Coarsening
stduy Edge-Based Image Coarseningstduy Edge-Based Image Coarsening
stduy Edge-Based Image Coarsening
Chiamin Hsu
 
satellite image processing
satellite image processingsatellite image processing
satellite image processing
avhadlaxmikant
 
Application of terrestrial 3D laser scanning in building information modellin...
Application of terrestrial 3D laser scanning in building information modellin...Application of terrestrial 3D laser scanning in building information modellin...
Application of terrestrial 3D laser scanning in building information modellin...
Martin Ma
 
Urban 3D Semantic Modelling Using Stereo Vision, ICRA 2013
Urban 3D Semantic Modelling Using Stereo Vision, ICRA 2013Urban 3D Semantic Modelling Using Stereo Vision, ICRA 2013
Urban 3D Semantic Modelling Using Stereo Vision, ICRA 2013
Sunando Sengupta
 
Object based image analysis tools for opticks
Object based image analysis tools for opticksObject based image analysis tools for opticks
Object based image analysis tools for opticks
Mohit Kumar
 
Ibica2014(p15)image fusion based on broveywavelet
Ibica2014(p15)image fusion based on broveywaveletIbica2014(p15)image fusion based on broveywavelet
Ibica2014(p15)image fusion based on broveywavelet
Aboul Ella Hassanien
 
RIM Poster Optics r2.1 - 2-OP-05 Glatzel_Tinsley Poster
RIM Poster Optics r2.1 - 2-OP-05 Glatzel_Tinsley PosterRIM Poster Optics r2.1 - 2-OP-05 Glatzel_Tinsley Poster
RIM Poster Optics r2.1 - 2-OP-05 Glatzel_Tinsley Poster
Kevin Nouri
 

Mais procurados (20)

Geoscience satellite image processing
Geoscience satellite image processingGeoscience satellite image processing
Geoscience satellite image processing
 
Satellite image processing
Satellite image processingSatellite image processing
Satellite image processing
 
Computer Science Thesis Defense
Computer Science Thesis DefenseComputer Science Thesis Defense
Computer Science Thesis Defense
 
stduy Edge-Based Image Coarsening
stduy Edge-Based Image Coarseningstduy Edge-Based Image Coarsening
stduy Edge-Based Image Coarsening
 
Visual Environment by Semantic Segmentation Using Deep Learning: A Prototype ...
Visual Environment by Semantic Segmentation Using Deep Learning: A Prototype ...Visual Environment by Semantic Segmentation Using Deep Learning: A Prototype ...
Visual Environment by Semantic Segmentation Using Deep Learning: A Prototype ...
 
Introduction to Mixed Reality
Introduction to Mixed RealityIntroduction to Mixed Reality
Introduction to Mixed Reality
 
Tracking Robustness and Green View Index Estimation of Augmented and Diminish...
Tracking Robustness and Green View Index Estimation of Augmented and Diminish...Tracking Robustness and Green View Index Estimation of Augmented and Diminish...
Tracking Robustness and Green View Index Estimation of Augmented and Diminish...
 
[Paper Presentation] Unbounded High Dynamic Range Photography using a Modulo ...
[Paper Presentation] Unbounded High Dynamic Range Photography using a Modulo ...[Paper Presentation] Unbounded High Dynamic Range Photography using a Modulo ...
[Paper Presentation] Unbounded High Dynamic Range Photography using a Modulo ...
 
satellite image processing
satellite image processingsatellite image processing
satellite image processing
 
Measuring and colouring M87
Measuring and colouring M87Measuring and colouring M87
Measuring and colouring M87
 
From pixels to point clouds - Using drones,game engines and virtual reality t...
From pixels to point clouds - Using drones,game engines and virtual reality t...From pixels to point clouds - Using drones,game engines and virtual reality t...
From pixels to point clouds - Using drones,game engines and virtual reality t...
 
Application of terrestrial 3D laser scanning in building information modellin...
Application of terrestrial 3D laser scanning in building information modellin...Application of terrestrial 3D laser scanning in building information modellin...
Application of terrestrial 3D laser scanning in building information modellin...
 
Looking from Above: Object Detection and Other Computer Vision Tasks on Satel...
Looking from Above: Object Detection and Other Computer Vision Tasks on Satel...Looking from Above: Object Detection and Other Computer Vision Tasks on Satel...
Looking from Above: Object Detection and Other Computer Vision Tasks on Satel...
 
Urban 3D Semantic Modelling Using Stereo Vision, ICRA 2013
Urban 3D Semantic Modelling Using Stereo Vision, ICRA 2013Urban 3D Semantic Modelling Using Stereo Vision, ICRA 2013
Urban 3D Semantic Modelling Using Stereo Vision, ICRA 2013
 
Object based image analysis tools for opticks
Object based image analysis tools for opticksObject based image analysis tools for opticks
Object based image analysis tools for opticks
 
Voxel based global-illumination
Voxel based global-illuminationVoxel based global-illumination
Voxel based global-illumination
 
30th コンピュータビジョン勉強会@関東 DynamicFusion
30th コンピュータビジョン勉強会@関東 DynamicFusion30th コンピュータビジョン勉強会@関東 DynamicFusion
30th コンピュータビジョン勉強会@関東 DynamicFusion
 
論文紹介"DynamicFusion: Reconstruction and Tracking of Non-­‐rigid Scenes in Real...
論文紹介"DynamicFusion: Reconstruction and Tracking of Non-­‐rigid Scenes in Real...論文紹介"DynamicFusion: Reconstruction and Tracking of Non-­‐rigid Scenes in Real...
論文紹介"DynamicFusion: Reconstruction and Tracking of Non-­‐rigid Scenes in Real...
 
Ibica2014(p15)image fusion based on broveywavelet
Ibica2014(p15)image fusion based on broveywaveletIbica2014(p15)image fusion based on broveywavelet
Ibica2014(p15)image fusion based on broveywavelet
 
RIM Poster Optics r2.1 - 2-OP-05 Glatzel_Tinsley Poster
RIM Poster Optics r2.1 - 2-OP-05 Glatzel_Tinsley PosterRIM Poster Optics r2.1 - 2-OP-05 Glatzel_Tinsley Poster
RIM Poster Optics r2.1 - 2-OP-05 Glatzel_Tinsley Poster
 

Destaque

ELSAYED ANTER METWALLY ATIA
ELSAYED ANTER METWALLY ATIAELSAYED ANTER METWALLY ATIA
ELSAYED ANTER METWALLY ATIA
sayed anter
 
Презентация проекта
Презентация проекта Презентация проекта
Презентация проекта
Mikhail Galeichenko
 
Teoria y practica_de_resistencia_de_materiales-_vigas
Teoria y practica_de_resistencia_de_materiales-_vigasTeoria y practica_de_resistencia_de_materiales-_vigas
Teoria y practica_de_resistencia_de_materiales-_vigas
Mely Mely
 
Sponsorbrochure A.S.R. Nereus
Sponsorbrochure A.S.R. NereusSponsorbrochure A.S.R. Nereus
Sponsorbrochure A.S.R. Nereus
Elwin van Rooijen
 
The Lost Art of Conversation
The Lost Art of ConversationThe Lost Art of Conversation
The Lost Art of Conversation
Laurenrinaldo
 

Destaque (20)

Sample AlbumStory: My Family
Sample AlbumStory: My FamilySample AlbumStory: My Family
Sample AlbumStory: My Family
 
Gravació del programa “El Gran Dictat”.
 Gravació del programa “El Gran Dictat”. Gravació del programa “El Gran Dictat”.
Gravació del programa “El Gran Dictat”.
 
Want your org to rise to the top? Look to your leaders.
Want your org to rise to the top? Look to your leaders.Want your org to rise to the top? Look to your leaders.
Want your org to rise to the top? Look to your leaders.
 
Quart de Primària. Visita a la deixalleria de Figueres.
Quart de Primària. Visita a la deixalleria de Figueres.Quart de Primària. Visita a la deixalleria de Figueres.
Quart de Primària. Visita a la deixalleria de Figueres.
 
Guest Lecture - UX Design in Jakamo, Timo Rossi 14 February 2017
Guest Lecture - UX Design in Jakamo, Timo Rossi 14 February 2017Guest Lecture - UX Design in Jakamo, Timo Rossi 14 February 2017
Guest Lecture - UX Design in Jakamo, Timo Rossi 14 February 2017
 
Gsm сигнализация Sapsan
Gsm сигнализация SapsanGsm сигнализация Sapsan
Gsm сигнализация Sapsan
 
ELSAYED ANTER METWALLY ATIA
ELSAYED ANTER METWALLY ATIAELSAYED ANTER METWALLY ATIA
ELSAYED ANTER METWALLY ATIA
 
Sarina Homes. Our Values: the #culturecode
Sarina Homes. Our Values: the #culturecodeSarina Homes. Our Values: the #culturecode
Sarina Homes. Our Values: the #culturecode
 
Презентация проекта
Презентация проекта Презентация проекта
Презентация проекта
 
Pastoral. Sant Josep de Calassanç 2016
Pastoral. Sant Josep de Calassanç 2016Pastoral. Sant Josep de Calassanç 2016
Pastoral. Sant Josep de Calassanç 2016
 
Teoria y practica_de_resistencia_de_materiales-_vigas
Teoria y practica_de_resistencia_de_materiales-_vigasTeoria y practica_de_resistencia_de_materiales-_vigas
Teoria y practica_de_resistencia_de_materiales-_vigas
 
P-5. Sortida a Serinyà.
P-5. Sortida a Serinyà.P-5. Sortida a Serinyà.
P-5. Sortida a Serinyà.
 
Tercer d'E.S.O. Tecnologia. Arbre de Nadal.
Tercer d'E.S.O. Tecnologia. Arbre de Nadal.Tercer d'E.S.O. Tecnologia. Arbre de Nadal.
Tercer d'E.S.O. Tecnologia. Arbre de Nadal.
 
falconer-sumuri
falconer-sumurifalconer-sumuri
falconer-sumuri
 
Celebració inici de curs
Celebració inici de cursCelebració inici de curs
Celebració inici de curs
 
Презентация достижений
Презентация достиженийПрезентация достижений
Презентация достижений
 
聖学院Net戦略2008年
聖学院Net戦略2008年聖学院Net戦略2008年
聖学院Net戦略2008年
 
Sponsorbrochure A.S.R. Nereus
Sponsorbrochure A.S.R. NereusSponsorbrochure A.S.R. Nereus
Sponsorbrochure A.S.R. Nereus
 
Capitulo4
Capitulo4Capitulo4
Capitulo4
 
The Lost Art of Conversation
The Lost Art of ConversationThe Lost Art of Conversation
The Lost Art of Conversation
 

Semelhante a Global illumination for PIXAR movie production

Synthesizing pseudo 2.5 d content from monocular videos for mixed reality
Synthesizing pseudo 2.5 d content from monocular videos for mixed realitySynthesizing pseudo 2.5 d content from monocular videos for mixed reality
Synthesizing pseudo 2.5 d content from monocular videos for mixed reality
NAVER Engineering
 
VERIFICATION_&_VALIDATION_OF_A_SEMANTIC_IMAGE_TAGGING_FRAMEWORK_VIA_GENERATIO...
VERIFICATION_&_VALIDATION_OF_A_SEMANTIC_IMAGE_TAGGING_FRAMEWORK_VIA_GENERATIO...VERIFICATION_&_VALIDATION_OF_A_SEMANTIC_IMAGE_TAGGING_FRAMEWORK_VIA_GENERATIO...
VERIFICATION_&_VALIDATION_OF_A_SEMANTIC_IMAGE_TAGGING_FRAMEWORK_VIA_GENERATIO...
grssieee
 
Nicolae_Denut_Theses
Nicolae_Denut_ThesesNicolae_Denut_Theses
Nicolae_Denut_Theses
Nicolae Denut
 
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
ijceronline
 

Semelhante a Global illumination for PIXAR movie production (20)

視訊訊號處理與深度學習應用
視訊訊號處理與深度學習應用視訊訊號處理與深度學習應用
視訊訊號處理與深度學習應用
 
Svr Raskar
Svr RaskarSvr Raskar
Svr Raskar
 
Synthesizing pseudo 2.5 d content from monocular videos for mixed reality
Synthesizing pseudo 2.5 d content from monocular videos for mixed realitySynthesizing pseudo 2.5 d content from monocular videos for mixed reality
Synthesizing pseudo 2.5 d content from monocular videos for mixed reality
 
stuart_2015_v2.0
stuart_2015_v2.0stuart_2015_v2.0
stuart_2015_v2.0
 
Detecting solar farms with deep learning
Detecting solar farms with deep learningDetecting solar farms with deep learning
Detecting solar farms with deep learning
 
VERIFICATION_&_VALIDATION_OF_A_SEMANTIC_IMAGE_TAGGING_FRAMEWORK_VIA_GENERATIO...
VERIFICATION_&_VALIDATION_OF_A_SEMANTIC_IMAGE_TAGGING_FRAMEWORK_VIA_GENERATIO...VERIFICATION_&_VALIDATION_OF_A_SEMANTIC_IMAGE_TAGGING_FRAMEWORK_VIA_GENERATIO...
VERIFICATION_&_VALIDATION_OF_A_SEMANTIC_IMAGE_TAGGING_FRAMEWORK_VIA_GENERATIO...
 
IRJET - Dehazing of Single Nighttime Haze Image using Superpixel Method
IRJET -  	  Dehazing of Single Nighttime Haze Image using Superpixel MethodIRJET -  	  Dehazing of Single Nighttime Haze Image using Superpixel Method
IRJET - Dehazing of Single Nighttime Haze Image using Superpixel Method
 
“A Computer Vision System for Autonomous Satellite Maneuvering,” a Presentati...
“A Computer Vision System for Autonomous Satellite Maneuvering,” a Presentati...“A Computer Vision System for Autonomous Satellite Maneuvering,” a Presentati...
“A Computer Vision System for Autonomous Satellite Maneuvering,” a Presentati...
 
Nicolae_Denut_Theses
Nicolae_Denut_ThesesNicolae_Denut_Theses
Nicolae_Denut_Theses
 
Resume_optics_Gupta Roy
Resume_optics_Gupta RoyResume_optics_Gupta Roy
Resume_optics_Gupta Roy
 
Build Your Own 3D Scanner: Conclusion
Build Your Own 3D Scanner: ConclusionBuild Your Own 3D Scanner: Conclusion
Build Your Own 3D Scanner: Conclusion
 
Uses of the OptIPortal
Uses of the OptIPortalUses of the OptIPortal
Uses of the OptIPortal
 
Transformer in Vision
Transformer in VisionTransformer in Vision
Transformer in Vision
 
Adoption of Software By A User Community: The Montage Image Mosaic Engine Exa...
Adoption of Software By A User Community: The Montage Image Mosaic Engine Exa...Adoption of Software By A User Community: The Montage Image Mosaic Engine Exa...
Adoption of Software By A User Community: The Montage Image Mosaic Engine Exa...
 
A Novel Background Subtraction Algorithm for Dynamic Texture Scenes
A Novel Background Subtraction Algorithm for Dynamic Texture ScenesA Novel Background Subtraction Algorithm for Dynamic Texture Scenes
A Novel Background Subtraction Algorithm for Dynamic Texture Scenes
 
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
 
PDS Imaging Node's Hosted Machine Learning Platform
PDS Imaging Node's Hosted Machine Learning PlatformPDS Imaging Node's Hosted Machine Learning Platform
PDS Imaging Node's Hosted Machine Learning Platform
 
ei2106-submit-opt-415
ei2106-submit-opt-415ei2106-submit-opt-415
ei2106-submit-opt-415
 
Feature Extraction Based Estimation of Rain Fall By Cross Correlating Cloud R...
Feature Extraction Based Estimation of Rain Fall By Cross Correlating Cloud R...Feature Extraction Based Estimation of Rain Fall By Cross Correlating Cloud R...
Feature Extraction Based Estimation of Rain Fall By Cross Correlating Cloud R...
 
Feature Extraction Based Estimation of Rain Fall By Cross Correlating Cloud R...
Feature Extraction Based Estimation of Rain Fall By Cross Correlating Cloud R...Feature Extraction Based Estimation of Rain Fall By Cross Correlating Cloud R...
Feature Extraction Based Estimation of Rain Fall By Cross Correlating Cloud R...
 

Último

Salient Features of India constitution especially power and functions
Salient Features of India constitution especially power and functionsSalient Features of India constitution especially power and functions
Salient Features of India constitution especially power and functions
KarakKing
 

Último (20)

How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17
 
Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentation
 
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
 
Spatium Project Simulation student brief
Spatium Project Simulation student briefSpatium Project Simulation student brief
Spatium Project Simulation student brief
 
HMCS Vancouver Pre-Deployment Brief - May 2024 (Web Version).pptx
HMCS Vancouver Pre-Deployment Brief - May 2024 (Web Version).pptxHMCS Vancouver Pre-Deployment Brief - May 2024 (Web Version).pptx
HMCS Vancouver Pre-Deployment Brief - May 2024 (Web Version).pptx
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdf
 
How to setup Pycharm environment for Odoo 17.pptx
How to setup Pycharm environment for Odoo 17.pptxHow to setup Pycharm environment for Odoo 17.pptx
How to setup Pycharm environment for Odoo 17.pptx
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024
 
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptxSKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
 
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
 
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
 
Wellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptxWellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptx
 
Unit 3 Emotional Intelligence and Spiritual Intelligence.pdf
Unit 3 Emotional Intelligence and Spiritual Intelligence.pdfUnit 3 Emotional Intelligence and Spiritual Intelligence.pdf
Unit 3 Emotional Intelligence and Spiritual Intelligence.pdf
 
Accessible Digital Futures project (20/03/2024)
Accessible Digital Futures project (20/03/2024)Accessible Digital Futures project (20/03/2024)
Accessible Digital Futures project (20/03/2024)
 
Understanding Accommodations and Modifications
Understanding  Accommodations and ModificationsUnderstanding  Accommodations and Modifications
Understanding Accommodations and Modifications
 
This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.
 
Salient Features of India constitution especially power and functions
Salient Features of India constitution especially power and functionsSalient Features of India constitution especially power and functions
Salient Features of India constitution especially power and functions
 

Global illumination for PIXAR movie production

  • 1. KAIST Computer Science Global illumination for PIXAR® movie production 20100121 Jaehyun Jang
  • 2. KAIST Computer Science • Global illumination for movie production • Current Lighting Computation Methods • Point-based Global Illumination for Movie Production • Physically-based Lighting at PIXAR • Global illumination researches in PIXAR® • Rendering Pipeline in Production (as a Rendering TD) Contents
  • 3. KAIST Computer Science • The first 3D animation used global illumination - Shrek 2 (2004) Global illumination for movie production Fig 1. Shrek 2. [Photograph]. Retrieved from http://www.awn.com/vfxworld/illuminating-global-illumination Courtesy of Paramount Pictures.
  • 4. KAIST Computer Science • Faking it : adding extra light sources labour intensive • Ray Tracing : requires many rays + shader evaluations Too much slow (at 2010!) • Radiosity Requires entire scene data on memory • Point-based Little memory, no shader evaluations Current Lighting Computation Method
  • 5. KAIST Computer Science Current : Physically-based Ray Tracing Fig 2. Monster University [Photograph]. Retrieved from http://neogaf.com/forum/showthread.php?t=569821 Courtesy of Disney-PIXAR • PIXAR has been rendering their movie using physically based ray-tracing after Monster University (2013)
  • 6. KAIST Computer Science Past : Point-based Global Illumination Techniques Fig 3. Toy Story 3 [Photograph]. Retrieved from http://graphics.pixar.com/library/PointBasedGlobalIlluminationForMovieProduction/ Courtesy of Disney-PIXAR • PIXAR uses point-based global illumination for rendering at 2010. At that time, ray- tracing cost is too high to render images.
  • 7. KAIST Computer Science • First introduced this technique in ‘Point-Based Approximate Color Bleeding’, (2008). • Background : Ray-tracing based global illumination is still expensive. • Advantages using point-based : 1. Fast Computation 2. Noisy-Free • Disadvantages : 1.Multi-pass approach, it cannot guarantee results as precise as ray tracing. Point-Based GI for Movie Production (2010)
  • 8. KAIST Computer Science Point-Based GI for Movie Production (2010) • Point Cloud Each point : position, normal, radius, color = a colored disk Color : the direct illumination at that surface position How to generate? : PRMan to tessellate the surfaces into small micropolygons, compute direct illumination from all light sources by using surface shader. —> This approach is “Baking the direct illumination” (TD Terminology)
  • 9. KAIST Computer Science Point-Based GI for Movie Production (2010) • Compute octree A bottom-up computation Consisting a node similar normals Compute a spherical harmonic from leaf-node Leaf-node : the sums of the coefficients for the surfels in the node. Non-leaf-node : the sums of the coefficients of its child nodes.
  • 10. KAIST Computer Science Point-Based GI for Movie Production (2010) Fig 4. Rasterization onto six raster cube faces [Photograph]. Retrieved from http:// graphics.pixar.com/library/ PointBasedGlobalIlluminationForMovieProducti on/ Courtesy of Disney-PIXAR • Compute diffuse, and glossy global illumination Traverse octree, visiting a node and rasterize the illumination from node. Rasterize colors contributing to a point : world “as seen” by that point (a low resolution fish-eye image) Convolution with the BRDF 1. loop over raster pixels and multiplying colors with the BRDF for the direction corresponding to that pixel. 2. Can deal with glossy global illumination
  • 11. KAIST Computer Science Point-Based GI for Movie Production (2010) Fig 5. Rendering with PRMan, baked radiosity value of point cloud (700,000 points) (left), glossy reflection (right) [Photograph]. Retrieved from http://penguin.ewu.edu/RenderMan/RMS_2.0/pointbased.html Courtesy of Disney-PIXAR
  • 12. KAIST Computer Science Point-Based GI for Movie Production (2010) • Variation and extensions Area light sources and soft shadows Environment illumination Multiple diffuse bounces Final gathering for photon mapping Ambient occlusion and reflection occlusion etc.
  • 13. KAIST Computer Science Point-Based GI for Movie Production (2010) Fig 6. Textured and displaced area light sources [Photograph]. Retrieved from http://penguin.ewu.edu/RenderMan/RMS_2.0/pointbased.html Courtesy of Disney-PIXAR
  • 14. KAIST Computer Science Point-Based GI for Movie Production (2010) Fig 7. Point cloud, Ambient occlusion, Reflection Occlusion, additional environment reflection [Photograph]. Retrieved from http://penguin.ewu.edu/RenderMan/RMS_2.0/pointbased.html Courtesy of Disney-PIXAR
  • 15. KAIST Computer Science • The lighting pipeline at PIXAR was completely rewritten and switched to a physically based and ray-traced system. • Rendering Equation L : radiance, f : BRDF 2 parts working in tandem : 1.Physically correct lights emitting energy in the scene 2.Physically correct BRDFs bouncing energy in the scene Physically based rendering pipeline (2013)
  • 16. KAIST Computer Science • Break down the rendering equation, each part will be solved by different coshaders(defined in RSL 2.0) called integrators (http://renderman.pixar.com/view/ coshaders) • ! ! • direct lighting integrator + indirect diffuse integrator + indirect specular integrator Physically based rendering pipeline (2013)
  • 17. KAIST Computer Science Fig 8. Light reflection [Photograph]. Retrieved from http://content.gpwiki.org/index.php/D3DBook: (Lighting)_Foundation_and_theory Courtesy of Wikimedia
  • 18. KAIST Computer Science • Direct Lighting Integrator (Coshader) 1.Sample from lobes using BRDF coshaders 2.Sample from lights using light coshaders 3.Combine samples using Multiple Importance Sampling (Ryusuke Villemin, et al. 2013). Physically based rendering pipeline (2013)
  • 19. KAIST Computer Science Fig 9. Structures communicates data between three coshaders consisting of Direct Light Integrator [Photograph]. Retrieved from http://graphics.pixar.com/library/PhysicallyBasedLighting/paper.pdf Courtesy of Disney-PIXAR
  • 20. KAIST Computer Science Algorithm 1. (Light Integration) Several algorithms in the paper : http://graphics.pixar.com/library/PhysicallyBasedLighting/paper.pdf
  • 21. KAIST Computer Science Fig 10. Various luminaries in this shot, The Blue Umbrella [Photograph]. Retrieved from http://graphics.pixar.com/library/PhysicallyBasedLighting/paper.pdf Courtesy of Disney-PIXAR
  • 22. KAIST Computer Science Fig 11. Physically-based lighting in Monster University [Photograph]. Retrieved from http://blog.selfshadow.com/publications/s2013-shading-course/pixar/ s2013_pbs_pixar_slides.pdf Courtesy of Disney-PIXAR
  • 23. KAIST Computer Science Fig 12. Physically-based lighting in Monster University [Photograph]. Retrieved from http://blog.selfshadow.com/publications/s2013-shading-course/pixar/ s2013_pbs_pixar_slides.pdf Courtesy of Disney-PIXAR
  • 24. KAIST Computer Science • Based on PIXAR online library (from 2011 - now) • Sampling Importance sampling 1. A statistical framework for comparing importance sampling methods, and an application to rectangular lights (Leonid Pekelis, et al. 2014). 2. Multiple Importance Sampling for Emissive Effects (Ryusuke Villemin, et al. 2013). 3. Importance Sampling of Reflections from Hair Fibers (Christophe Hery, et al. 2011). Stratified Sampling 1. Correlated Multi-Jittered Sampling (Andrew Kensler, 2013). Global Illumination Researches in PIXAR
  • 25. KAIST Computer Science • Caching 1. Multiresolution Radiosity Caching for Efficient Preview and Final Quality Global Illumination in Movies (Per H. Christensen, et al. 2012) • Summary PIXAR researches physically-based ray tracing, their rendering pipeline running on monte-carlo ray tracing, and it needs to develop proper sampling techniques for BRDF and etc. Global Illumination Researches in PIXAR
  • 26. KAIST Computer Science • Physically-based rendering is production standard. • Current PRMan® pipeline, RSL 2.0 supports physically plausible shaders. • For rendering technical directors, these kind of techniques are tremendously demanded. • — All is commented by technical director in PIXAR. Rendering Pipeline in Production