Biased Monte Carlo Ray Tracing
|
|
- Marianna Floyd
- 6 years ago
- Views:
Transcription
1 Biased Monte Carlo Ray Tracing Filtering, Irradiance Caching, and Photon Mapping Henrik Wann Jensen Stanford University May 23, 2002
2 Unbiased and Consistent Unbiased estimator: E{X} =... Consistent estimator: lim E{X} N...
3 Unbiased and Consistent Unbiased estimator: 1 N N i=1 f(ξ i ) Consistent estimator: 1 N + 1 N f(ξ i ) i=1
4 Unbiased Methods Variance (noise) is the only error This error can be analyzed using the variance (i.e. 95% of samples are within 2% of the correct result)
5 Path Tracing (Unbiased) 10 paths/pixel
6 Path Tracing (Unbiased) 10 paths/pixel
7 Path Tracing (Unbiased) 100 paths/pixel
8 How Can We Remove This Noise
9 The World is Diffuse! Arnold Rendering
10 The World is Diffuse! Arnold Rendering
11 The World is Diffuse! Arnold Rendering
12 Noise Reduction/Removal More samples (slow convergence, σ 1/ N)
13 Noise Reduction/Removal More samples (slow convergence, σ 1/ N) Better sampling (stratified, importance, qmc etc.)
14 Noise Reduction/Removal More samples (slow convergence, σ 1/ N) Better sampling (stratified, importance, qmc etc.) Adaptive sampling
15 Noise Reduction/Removal More samples (slow convergence, σ 1/ N) Better sampling (stratified, importance, qmc etc.) Adaptive sampling Filtering
16 Noise Reduction/Removal More samples (slow convergence, σ 1/ N) Better sampling (stratified, importance, qmc etc.) Adaptive sampling Filtering Caching and interpolation
17 Stratified Sampling Latin Hypercube: 10 paths/pixel
18 Quasi Monte-Carlo Halton-Sequence: 10 paths/pixel
19 Fixed (Random) Sequence 10 paths/pixel
20 Filtering: Idea Noise is high frequency
21 Filtering: Idea Noise is high frequency Remove high frequency content
22 Unfiltered Image 10 paths/pixel
23 3x3 Lowpass Filter 10 paths/pixel
24 Unfiltered Image 10 paths/pixel
25 3x3 Median Filter 10 paths/pixel
26 Energy Preserving Filters
27 Energy Preserving Filters Distribute noisy energy over several pixels
28 Energy Preserving Filters Distribute noisy energy over several pixels Adaptive filter width [Rushmeier and Ward 94] Diffusion style filters [McCool99] Splatting style filters [Suykens and Willems 00]
29 Problems With Filtering Everything is filtered (blurred) Textures Highlights Caustics...
30 Caching Techniques
31 Caching Techniques Irradiance caching : Compute irradiance at selected points and interpolate. Photon mapping : Trace ``photons'' from the lights and store them in a photon map, that can be used during rendering.
32 Box: Direct Illlumination
33 Box: Global Illlumination
34 Box: Indirect Irradiance
35 Irradiance Caching: Idea ``A Ray Tracing Solution for Diffuse Interreflection''. Greg Ward, Francis Rubinstein and Robert Clear: Proc. SIGGRAPH'88. Idea: Irradiance changes slowly interpolate.
36 Irradiance Sampling E(x) = 2π L (x, ω ) cos θ dω
37 Irradiance Sampling E(x) = = L (x, ω ) cos θ dω 2π 2π π/2 0 0 L (x, θ, φ) cos θ sin θ dθ dφ
38 Irradiance Sampling E(x) = = 0 L (x, ω ) cos θ dω 2π 2π π/2 π T P 0 T t=1 L (x, θ, φ) cos θ sin θ dθ dφ P p=1 L (θ t, φ p ) θ t = sin 1 ( ) t ξ T and φ p = 2π p ψ P
39 Irradiance Change ɛ(x) E x (x x 0) + E θ (θ θ 0) } {{ } } {{ } position rotation
40 Irradiance Change ɛ(x) E x (x x 0) + E θ (θ θ 0) } {{ } } {{ } position rotation ( ) 4 x x 0 E N(x) π x N(x 0 ) avg } {{ } } {{ } position rotation
41 Irradiance Interpolation w(x) = 1 ɛ(x) 1 x x 0 1 N(x) N(x 0 ) x avg + E i (x) = i w i (x)e(x i ) w i (x) i
42 Irradiance Caching Algorithm Find all irradiance samples with w(x) > q if (samples found) interpolate else compute new irradiance sample
43 Box: Irradiance Caching 1000 sample rays, w>10
44 Box: Irradiance Cache Positions 1000 sample rays, w>10
45 Box: Irradiance Caching 1000 sample rays, w>20
46 Box: Irradiance Cache Positions 1000 sample rays, w>20
47 Box: Irradiance Caching 5000 sample rays, w>10
48 Box: Irradiance Cache Positions 5000 sample rays, w>10
49 Caustics Pathtracing 1000 paths/pixel
50 A simple test scene
51 Rendering
52 Photon Tracing
53 Photons
54 Radiance Estimate L(x, ω) = Ω f r (x, ω, ω)l (x, ω ) cos θ dω
55 Radiance Estimate L(x, ω) = = Ω Ω f r (x, ω, ω)l (x, ω ) cos θ dω f r (x, ω, ω) dφ2 (x, ω ) dω cos θ da cos θ dω
56 Radiance Estimate L(x, ω) = = = Ω Ω Ω f r (x, ω, ω)l (x, ω ) cos θ dω f r (x, ω, ω) dφ2 (x, ω ) dω cos θ da cos θ dω f r (x, ω, ω) dφ2 (x, ω ) da
57 Radiance Estimate L(x, ω) = = = f r (x, ω, ω)l (x, ω ) cos θ dω Ω f r (x, ω, ω) dφ2 (x, ω ) Ω dω cos θ da cos θ dω f r (x, ω, ω) dφ2 (x, ω ) Ω da n f r (x, ω p, ω) Φ p(x, ω p) πr 2 p=1
58 Radiance Estimate L
59 The photon map datastructure The photons are stored in a left balanced kd-tree struct photon = { float position[3]; rgbe power; char phi, theta; short flags; } // power packed as 4 bytes // incoming direction
60 Rendering: Caustics
61 Caustic from a Glass Sphere Photon Mapping: photons / 50 photons in radiance estimate
62 Caustic from a Glass Sphere Path Tracing: 1000 paths/pixel
63 Sphereflake Caustic
64 Reflection Inside A Metal Ring photons / 50 photons in radiance estimate
65 Caustics On Glossy Surfaces photons / 100 photons in radiance estimate
66 HDR environment illumination Using lightprobe from
67 Cognac Glass
68 Cube Caustic
69 Global Illumination photons / 50 photons in radiance estimate
70 Global Illumination photons / 500 photons in radiance estimate
71 Fast estimate 200 photons / 50 photons in radiance estimate
72 Indirect illumination photons / 500 photons in radiance estimate
73 Global Illumination
74 Global Illumination global photon map caustics photon map
75 Photon tracing Photon emission Photon scattering Photon storing
76 Photon emission Given Φ Watt lightbulb. Emit N photons. Each photon has the power Φ N Watt. Photon power depends on the number of emitted photons. Not on the number of photons in the photon map.
77 What is a photon? Flux (power) - not radiance! Collection of physical photons A fraction of the light source power Several wavelengths combined into one entity
78 Diffuse point light Generate random direction Emit photon in that direction // Find random direction do { x = 2.0*random()-1.0; y = 2.0*random()-1.0; z = 2.0*random()-1.0; } while ( (x*x + y*y + z*z) > 1.0 );
79 Example: Diffuse square light - Generate random position p on square - Generate diffuse direction d - Emit photon from p in direction d // Generate diffuse direction u = random(); v = 2*π*random(); d = vector( cos(v) u, sin(v) u, 1 u );
80 Surface interactions The photon is Stored (at diffuse surfaces) and Absorbed (A) or Reflected (R) or Transmitted (T ) A + R + T = 1.0
81 Photon scattering The simple way: Given incoming photon with power Φ p Reflect photon with the power R Φ p Transmit photon with the power T Φ p
82 Photon scattering The simple way: Given incoming photon with power Φ p Reflect photon with the power R Φ p Transmit photon with the power T Φ p Risk: Too many low-powered photons - wasteful! When do we stop (systematic bias)? Photons with similar power is a good thing.
83 Russian Roulette Statistical technique Known from Monte Carlo particle physics Introduced to graphics by Arvo and Kirk in 1990
84 Russian Roulette Probability of termination: p
85 Russian Roulette Probability of termination: p E{X}
86 Russian Roulette Probability of termination: p E{X} = p 0
87 Russian Roulette Probability of termination: p E{X} = p 0 + (1 p)
88 Russian Roulette Probability of termination: p E{X} = p 0 + (1 p) E{X} 1 p
89 Russian Roulette Probability of termination: p E{X} = p 0 + (1 p) E{X} 1 p = E{X}
90 Russian Roulette Probability of termination: p E{X} = p 0 + (1 p) E{X} 1 p = E{X} Terminate un-important photons and still get the correct result.
91 Russian Roulette Example Surface reflectance: R = 0.5 Incoming photon: Φ p = 2 W r = random(); if ( r < 0.5 ) reflect photon with power 2 W else photon is absorbed
92 Russian Roulette Intuition Surface reflectance: R = incoming photons with power: Φ p = 2 Watt Reflect 100 photons with power 2 Watt instead of 200 photons with power 1 Watt.
93 Russian Roulette Very important! Use to eliminate un-important photons Gives photons with similar power :)
94 Sampling a BRDF f r (x, ω i, ω o ) = w 1 f r,1 (x, ω i, ω o ) + w 2 f r,2 (x, ω i, ω o )
95 Sampling a BRDF f r (x, ω i, ω o ) = w 1 f r,d + w 2 f r,s r = random() (w 1 + w 2 ); if ( r < w 1 ) reflect diffuse photon else reflect specular
96 Rendering
97 Direct Illumination
98 Specular Reflection
99 Caustics
100 Indirect Illumination
101 Rendering Equation Solution L r (x, ω) = = f r (x, ω, ω)l i (x, ω ) cos θ i dω i Ω x Ω x f r (x, ω, ω)l i,l (x, ω ) cos θ i dω i + Ω x f r,s (x, ω, ω)(l i,c (x, ω ) + L i,d (x, ω )) cos θ i dω i + Ω x f r,d (x, ω, ω)l i,c (x, ω ) cos θ i dω i + Ω x f r,d (x, ω, ω)l i,d (x, ω ) cos θ i dω i.
102 Features Photon tracing is unbiased Radiance estimate is biased but consistent The reconstruction error is local Illumination representation is decoupled from the geometry
103 Box global photons, caustic photons
104 Box: Global Photons global photons
105 Fractal Box global photons, caustic photons
106 Cornell Box
107 Indirect Illumination
108 Little Matterhorn
109 Mies house (swimmingpool)
110 Mies house (3pm)
111 Mies house (6pm)
112 More Information Foreword by Pat Hanrahan The creation of realistic three-dimensional images is central to computer graphics. Photon mapping, an extension of ray tracing, makes it possible to efficiently simulate global illumination in complex scenes. Photo mapping can simulate caustics (focused light, such as shimmering waves at the bottom of a swimming pool), diffuse inter-reflections (e.g., the `bleeding' of colored light from a red wall onto a white floor, giving the floor a reddish tint), and participating media (e.g., clouds or smoke). This book is a practical guide to photon mapping; it provides both the theory and the practical insight necessary to implement photon mapping and simulate all types of direct and indirect illumination efficiently. A K PETERS LTD. Realistic Image Synthesis Using Photon Mapping Realistic Image Synthesis Using Photon Mapping Jensen Henrik Wann Jensen AK PETERS Henrik Wann Jensen Realistic Image Synthesis Using Photon Mapping Foreword by Pat Hanrahan henrik@graphics.stanford.edu
Biased Monte Carlo Ray Tracing:
Biased Monte Carlo Ray Tracing: Filtering, Irradiance Caching and Photon Mapping Dr. Henrik Wann Jensen Stanford University May 24, 2001 Unbiased and consistent Monte Carlo methods Unbiased estimator:
More informationDiscussion. Smoothness of Indirect Lighting. History and Outline. Irradiance Calculation. Irradiance Caching. Advanced Computer Graphics (Spring 2013)
Advanced Computer Graphics (Spring 2013 CS 283, Lecture 12: Recent Advances in Monte Carlo Offline Rendering Ravi Ramamoorthi http://inst.eecs.berkeley.edu/~cs283/sp13 Some slides/ideas courtesy Pat Hanrahan,
More informationTo Do. Real-Time High Quality Rendering. Motivation for Lecture. Monte Carlo Path Tracing. Monte Carlo Path Tracing. Monte Carlo Path Tracing
Real-Time High Quality Rendering CSE 274 [Fall 2015], Lecture 5 Tour of Modern Offline Rendering To Do Project milestone (1-2 pages), final project proposal Due on Oct 27 Please get in touch with me if
More informationMIT Monte-Carlo Ray Tracing. MIT EECS 6.837, Cutler and Durand 1
MIT 6.837 Monte-Carlo Ray Tracing MIT EECS 6.837, Cutler and Durand 1 Schedule Review Session: Tuesday November 18 th, 7:30 pm bring lots of questions! Quiz 2: Thursday November 20 th, in class (one weeks
More informationGlobal Illumination using Photon Maps
This paper is a slightly extended version of the paper in Rendering Techniques 96 (Proceedings of the Seventh Eurographics Workshop on Rendering), pages 21 30, 1996 Global Illumination using Photon Maps
More informationSchedule. MIT Monte-Carlo Ray Tracing. Radiosity. Review of last week? Limitations of radiosity. Radiosity
Schedule Review Session: Tuesday November 18 th, 7:30 pm, Room 2-136 bring lots of questions! MIT 6.837 Monte-Carlo Ray Tracing Quiz 2: Thursday November 20 th, in class (one weeks from today) MIT EECS
More informationMotivation. Advanced Computer Graphics (Fall 2009) CS 283, Lecture 11: Monte Carlo Integration Ravi Ramamoorthi
Advanced Computer Graphics (Fall 2009) CS 283, Lecture 11: Monte Carlo Integration Ravi Ramamoorthi http://inst.eecs.berkeley.edu/~cs283 Acknowledgements and many slides courtesy: Thomas Funkhouser, Szymon
More informationPhoton Mapping. Michael Doggett Department of Computer Science Lund university
Photon Mapping Michael Doggett Department of Computer Science Lund university Outline Photon Mapping (ch. 14 in textbook) Progressive Stochastic 2011 Michael Doggett How to make light sampling faster?
More informationKorrigeringar: An introduction to Global Illumination. Global Illumination. Examples of light transport notation light
An introduction to Global Illumination Tomas Akenine-Möller Department of Computer Engineering Chalmers University of Technology Korrigeringar: Intel P4 (200): ~42M transistorer Intel P4 EE (2004): 78M
More informationRecent Advances in Monte Carlo Offline Rendering
CS294-13: Special Topics Lecture #6 Advanced Computer Graphics University of California, Berkeley Monday, 21 September 2009 Recent Advances in Monte Carlo Offline Rendering Lecture #6: Monday, 21 September
More informationMotivation: Monte Carlo Path Tracing. Sampling and Reconstruction of Visual Appearance. Monte Carlo Path Tracing. Monte Carlo Path Tracing
Sampling and Reconstruction of Visual Appearance CSE 274 [Winter 2018], Lecture 4 Ravi Ramamoorthi http://www.cs.ucsd.edu/~ravir Motivation: Key application area for sampling/reconstruction Core method
More informationStochastic Path Tracing and Image-based lighting
EDA101 : Advanced Shading and Rendering Stochastic Path Tracing and Image-based lighting Michael Doggett 2008 Tomas Akenine-Möller 1 This is what we want: Courtesy of Henrik Wann Jensen Courtesy of Paul
More informationRaytracing & Epsilon. Today. Last Time? Forward Ray Tracing. Does Ray Tracing Simulate Physics? Local Illumination
Raytracing & Epsilon intersects light @ t = 25.2 intersects sphere1 @ t = -0.01 & Monte Carlo Ray Tracing intersects sphere1 @ t = 10.6 Solution: advance the ray start position epsilon distance along the
More informationMonte-Carlo Ray Tracing. Antialiasing & integration. Global illumination. Why integration? Domains of integration. What else can we integrate?
Monte-Carlo Ray Tracing Antialiasing & integration So far, Antialiasing as signal processing Now, Antialiasing as integration Complementary yet not always the same in particular for jittered sampling Image
More informationGlobal Illumination. CSCI 420 Computer Graphics Lecture 18. BRDFs Raytracing and Radiosity Subsurface Scattering Photon Mapping [Ch
CSCI 420 Computer Graphics Lecture 18 Global Illumination Jernej Barbic University of Southern California BRDFs Raytracing and Radiosity Subsurface Scattering Photon Mapping [Ch. 13.4-13.5] 1 Global Illumination
More information2/1/10. Outline. The Radiance Equation. Light: Flux Equilibrium. Light: Radiant Power. Light: Equation. Radiance. Jan Kautz
Outline Jan Kautz Basic terms in radiometry Radiance Reflectance The operator form of the radiance equation Meaning of the operator form Approximations to the radiance equation 2005 Mel Slater, 2006 Céline
More informationGlobal Illumination. Global Illumination. Direct Illumination vs. Global Illumination. Indirect Illumination. Soft Shadows.
CSCI 420 Computer Graphics Lecture 18 Global Illumination Jernej Barbic University of Southern California BRDFs Raytracing and Radiosity Subsurface Scattering Photon Mapping [Angel Ch. 11] 1 Global Illumination
More informationPart I The Basic Algorithm. Principles of Photon Mapping. A two-pass global illumination method Pass I Computing the photon map
Part I The Basic Algorithm 1 Principles of A two-pass global illumination method Pass I Computing the photon map A rough representation of the lighting in the scene Pass II rendering Regular (distributed)
More informationMotivation. Monte Carlo Path Tracing. Monte Carlo Path Tracing. Monte Carlo Path Tracing. Monte Carlo Path Tracing
Advanced Computer Graphics (Spring 2013) CS 283, Lecture 11: Monte Carlo Path Tracing Ravi Ramamoorthi http://inst.eecs.berkeley.edu/~cs283/sp13 Motivation General solution to rendering and global illumination
More informationGlobal Illumination. Global Illumination. Direct Illumination vs. Global Illumination. Indirect Illumination. Soft Shadows.
CSCI 480 Computer Graphics Lecture 18 Global Illumination BRDFs Raytracing and Radiosity Subsurface Scattering Photon Mapping [Ch. 13.4-13.5] March 28, 2012 Jernej Barbic University of Southern California
More informationThe Rendering Equation and Path Tracing
The Rendering Equation and Path Tracing Louis Feng April 22, 2004 April 21, 2004 Realistic Image Synthesis (Spring 2004) 1 Topics The rendering equation Original form Meaning of the terms Integration Path
More informationAdvanced Graphics. Path Tracing and Photon Mapping Part 2. Path Tracing and Photon Mapping
Advanced Graphics Path Tracing and Photon Mapping Part 2 Path Tracing and Photon Mapping Importance Sampling Combine importance sampling techniques Reflectance function (diffuse + specular) Light source
More informationChoosing the Right Algorithm & Guiding
Choosing the Right Algorithm & Guiding PHILIPP SLUSALLEK & PASCAL GRITTMANN Topics for Today What does an implementation of a high-performance renderer look like? Review of algorithms which to choose for
More informationFinal Project: Real-Time Global Illumination with Radiance Regression Functions
Volume xx (200y), Number z, pp. 1 5 Final Project: Real-Time Global Illumination with Radiance Regression Functions Fu-Jun Luan Abstract This is a report for machine learning final project, which combines
More informationThe Rendering Equation. Computer Graphics CMU /15-662, Fall 2016
The Rendering Equation Computer Graphics CMU 15-462/15-662, Fall 2016 Review: What is radiance? Radiance at point p in direction N is radiant energy ( #hits ) per unit time, per solid angle, per unit area
More informationThe Rendering Equation. Computer Graphics CMU /15-662
The Rendering Equation Computer Graphics CMU 15-462/15-662 Review: What is radiance? Radiance at point p in direction N is radiant energy ( #hits ) per unit time, per solid angle, per unit area perpendicular
More informationPath Tracing part 2. Steve Rotenberg CSE168: Rendering Algorithms UCSD, Spring 2017
Path Tracing part 2 Steve Rotenberg CSE168: Rendering Algorithms UCSD, Spring 2017 Monte Carlo Integration Monte Carlo Integration The rendering (& radiance) equation is an infinitely recursive integral
More informationA Brief Overview of. Global Illumination. Thomas Larsson, Afshin Ameri Mälardalen University
A Brief Overview of Global Illumination Thomas Larsson, Afshin Ameri Mälardalen University 1 What is Global illumination? Global illumination is a general name for realistic rendering algorithms Global
More information11/2/2010. In the last lecture. Monte-Carlo Ray Tracing : Path Tracing. Today. Shadow ray towards the light at each vertex. Path Tracing : algorithm
Comuter Grahics Global Illumination: Monte-Carlo Ray Tracing and Photon Maing Lecture 11 In the last lecture We did ray tracing and radiosity Ray tracing is good to render secular objects but cannot handle
More informationLecture 7: Monte Carlo Rendering. MC Advantages
Lecture 7: Monte Carlo Rendering CS 6620, Spring 2009 Kavita Bala Computer Science Cornell University MC Advantages Convergence rate of O( ) Simple Sampling Point evaluation Can use black boxes General
More informationPhoton Mapping. Due: 3/24/05, 11:59 PM
CS224: Interactive Computer Graphics Photon Mapping Due: 3/24/05, 11:59 PM 1 Math Homework 20 Ray Tracing 20 Photon Emission 10 Russian Roulette 10 Caustics 15 Diffuse interreflection 15 Soft Shadows 10
More informationMonte Carlo Ray Tracing. Computer Graphics CMU /15-662
Monte Carlo Ray Tracing Computer Graphics CMU 15-462/15-662 TODAY: Monte Carlo Ray Tracing How do we render a photorealistic image? Put together many of the ideas we ve studied: - color - materials - radiometry
More informationPhoton Mapping. Kadi Bouatouch IRISA
Kadi Bouatouch IRISA Email: kadi@irisa.fr 1 Photon emission and transport 2 Photon caching 3 Spatial data structure for fast access 4 Radiance estimation 5 Kd-tree Balanced Binary Tree When a splitting
More informationIntroduction to Photon Mapping RADIANCE Workshop 2010 Course Advanced Fenestration
Introduction to Photon Mapping RADIANCE Workshop 2010 Course Advanced Fenestration Roland Schregle Motivation: Caustics Light transport from specular surfaces gives rise to caustics on diffuse surfaces.
More informationCS 563 Advanced Topics in Computer Graphics Irradiance Caching and Particle Tracing. by Stephen Kazmierczak
CS 563 Advanced Topics in Computer Graphics Irradiance Caching and Particle Tracing by Stephen Kazmierczak Introduction Unbiased light transport algorithms can sometimes take a large number of rays to
More informationLecture 12: Photon Mapping. Biased Methods
Lecture 12: Photon Mapping CS 6620, Spring 2009 Kavita Bala Computer Science Cornell University MC problems Biased Methods Biased methods: store information (caching) Better type of noise: blurring Greg
More informationMonte Carlo Path Tracing. The Rendering Equation
Monte Carlo Path Tracing Today Path tracing starting from the eye Path tracing starting from the lights Which direction is best? Bidirectional ray tracing Random walks and Markov chains Next Irradiance
More informationAn introduction to Global Illumination. Tomas Akenine-Möller Department of Computer Engineering Chalmers University of Technology
An introduction to Global Illumination Tomas Akenine-Möller Department of Computer Engineering Chalmers University of Technology Misc Till alla lärare på masternivån, Undervisningen på Chalmers masterprogram
More informationLecture 7 - Path Tracing
INFOMAGR Advanced Graphics Jacco Bikker - November 2016 - February 2017 Lecture 7 - I x, x = g(x, x ) ε x, x + S ρ x, x, x I x, x dx Welcome! Today s Agenda: Introduction Advanced Graphics 3 Introduction
More informationMotivation: Monte Carlo Rendering. Sampling and Reconstruction of Visual Appearance. Caustics. Illumination Models. Overview of lecture.
Sampling and Reconstruction of Visual Appearance CSE 74 [Winter 8], Lecture 3 Ravi Ramamoorthi http://www.cs.ucsd.edu/~ravir Motivation: Monte Carlo Rendering Key application area for sampling/reconstruction
More informationAssignment 3: Path tracing
Assignment 3: Path tracing EDAN30 April 2, 2011 In this assignment you will be asked to extend your ray tracer to support path tracing. In order to pass the assignment you need to complete all tasks. Make
More informationIllumination Algorithms
Global Illumination Illumination Algorithms Digital Lighting and Rendering CGT 340 The goal of global illumination is to model all possible paths of light to the camera. Global Illumination Global illumination
More informationPhoton Differentials
Photon Differentials Adaptive Anisotropic Density Estimation in Photon Mapping Jeppe Revall Frisvad Technical University of Denmark Trade-off problem in photon mapping Effect of changing bandwidth (no.
More informationPhoton Maps. The photon map stores the lighting information on points or photons in 3D space ( on /near 2D surfaces)
Photon Mapping 1/36 Photon Maps The photon map stores the lighting information on points or photons in 3D space ( on /near 2D surfaces) As opposed to the radiosity method that stores information on surface
More informationLow Memory Spectral Photon Mapping
Low Memory Spectral Photon Mapping Antoine Boudet 1,2, Mathias Paulin 1, Paul Pitot 2, and David Pratmarty 2 1 IRIT-UPS-CNRS, University Paul Sabatier, Toulouse, France 2 OKTAL SE, Toulouse, France Abstract
More informationPath differentials and applications
Path differentials and applications Frank Suykens, Yves D. Willems Department of Computer Science, K.U.Leuven, Belgium Frank.Suykens@cs.kuleuven.ac.be Abstract. Photo-realistic rendering algorithms such
More informationrendering equation computer graphics rendering equation 2009 fabio pellacini 1
rendering equation computer graphics rendering equation 2009 fabio pellacini 1 physically-based rendering synthesis algorithms that compute images by simulation the physical behavior of light computer
More informationTHE goal of rendering algorithms is to synthesize images of virtual scenes. Global illumination
2 Fundamentals of Light Transport He who loves practice without theory is like the sailor who boards ship without a rudder and compass and never knows where he may cast. Leonardo Da Vinci, 1452 1519 THE
More informationSpectral Color and Radiometry
Spectral Color and Radiometry Louis Feng April 13, 2004 April 13, 2004 Realistic Image Synthesis (Spring 2004) 1 Topics Spectral Color Light and Color Spectrum Spectral Power Distribution Spectral Color
More informationMonte Carlo Ray-tracing and Rendering
ITN, Norrko ping February 3, 2012 Monte Carlo Ray-tracing and Rendering P ROJECT IN A DVANCED G LOBAL I LLUMINATION AND R ENDERING TNCG15 Authors: Henrik Ba cklund Niklas Neijman Contact: henba892@student.liu.se
More informationGlobal Illumination with Glossy Surfaces
Global Illumination with Glossy Surfaces Wolfgang Stürzlinger GUP, Johannes Kepler Universität, Altenbergerstr.69, A-4040 Linz, Austria/Europe wrzl@gup.uni-linz.ac.at Abstract Photorealistic rendering
More informationGlobal Illumination and Monte Carlo
Global Illumination and Monte Carlo MIT EECS 6.837 Computer Graphics Wojciech Matusik with many slides from Fredo Durand and Jaakko Lehtinen ACM. All rights reserved. This content is excluded from our
More informationImproved Illumination Estimation for Photon Maps in Architectural Scenes
Improved Illumination Estimation for Photon Maps in Architectural Scenes Robert F. Tobler VRVis Research Center Donau-City Str. 1/3 1120 Wien, Austria rft@vrvis.at Stefan Maierhofer VRVis Research Center
More information6. Illumination, Lighting
Jorg s Graphics Lecture Notes 6. Illumination, Lighting 1 6. Illumination, Lighting No ray tracing in OpenGL! ray tracing: direct paths COP interreflection: soft shadows, color bleeding. umbra, penumbra,
More informationRendering Algorithms: Real-time indirect illumination. Spring 2010 Matthias Zwicker
Rendering Algorithms: Real-time indirect illumination Spring 2010 Matthias Zwicker Today Real-time indirect illumination Ray tracing vs. Rasterization Screen space techniques Visibility & shadows Instant
More informationIrradiance Gradients. Media & Occlusions
Irradiance Gradients in the Presence of Media & Occlusions Wojciech Jarosz in collaboration with Matthias Zwicker and Henrik Wann Jensen University of California, San Diego June 23, 2008 Wojciech Jarosz
More informationReflection models and radiometry Advanced Graphics
Reflection models and radiometry Advanced Graphics Rafał Mantiuk Computer Laboratory, University of Cambridge Applications To render realistic looking materials Applications also in computer vision, optical
More informationVirtual Spherical Lights for Many-Light Rendering of Glossy Scenes
Virtual Spherical Lights for Many-Light Rendering of Glossy Scenes Miloš Hašan Jaroslav Křivánek * Bruce Walter Kavita Bala Cornell University * Charles University in Prague Global Illumination Effects
More informationImportance Sampling of Area Lights in Participating Media
Importance Sampling of Area Lights in Participating Media Christopher Kulla Marcos Fajardo Outline Previous Work Single Scattering Equation Importance Sampling for Point Lights Importance Sampling for
More informationThe Rendering Equation Philip Dutré. Course 4. State of the Art in Monte Carlo Global Illumination Sunday, Full Day, 8:30 am - 5:30 pm
The Rendering Equation Philip Dutré Course 4. State of the Art in Monte Carlo Global Illumination Sunday, Full Day, 8:30 am - 5:30 pm 1 Overview Rendering Equation Path tracing Path Formulation Various
More informationMonte Carlo Integration of The Rendering Equation. Computer Graphics CMU /15-662, Spring 2017
Monte Carlo Integration of The Rendering Equation Computer Graphics CMU 15-462/15-662, Spring 2017 Review: Monte Carlo integration Z b Definite integral What we seek to estimate a f(x)dx Random variables
More informationInteractive Rendering of Globally Illuminated Glossy Scenes
Interactive Rendering of Globally Illuminated Glossy Scenes Wolfgang Stürzlinger, Rui Bastos Dept. of Computer Science, University of North Carolina at Chapel Hill {stuerzl bastos}@cs.unc.edu Abstract.
More informationPhilipp Slusallek Karol Myszkowski. Realistic Image Synthesis SS18 Instant Global Illumination
Realistic Image Synthesis - Instant Global Illumination - Karol Myszkowski Overview of MC GI methods General idea Generate samples from lights and camera Connect them and transport illumination along paths
More informationGlobal Illumination CS334. Daniel G. Aliaga Department of Computer Science Purdue University
Global Illumination CS334 Daniel G. Aliaga Department of Computer Science Purdue University Recall: Lighting and Shading Light sources Point light Models an omnidirectional light source (e.g., a bulb)
More informationTo Do. Advanced Computer Graphics. Course Outline. Course Outline. Illumination Models. Diffuse Interreflection
Advanced Computer Graphics CSE 163 [Spring 017], Lecture 11 Ravi Ramamoorthi http://www.cs.ucsd.edu/~ravir To Do Assignment due May 19 Should already be well on way. Contact us for difficulties etc. This
More informationBRDFs. Steve Rotenberg CSE168: Rendering Algorithms UCSD, Spring 2017
BRDFs Steve Rotenberg CSE168: Rendering Algorithms UCSD, Spring 2017 The Rendering Equation Radiance Radiance is a measure of the quantity of light radiation reflected (and/or emitted) from a surface within
More informationEfficient Simulation of Light Transport in Scenes with Participating Media using Photon Maps
Efficient Simulation of ight Transport in Scenes ith Participating Media using Photon Maps Paper by Henrik Wann Jensen Per H. Christensen Presented by Abhinav Golas 1 Overvie What is participative media?
More informationRealistic Image Synthesis
Realistic Image Synthesis - BRDFs and Direct ighting - Philipp Slusalle Karol Myszowsi Gurprit Singh Realistic Image Synthesis SS8 BRDFs and Direct ighting Importance Sampling Example Example: Generate
More informationAdvanced Graphics. Global Illumination. Alex Benton, University of Cambridge Supported in part by Google UK, Ltd
Advanced Graphics Global Illumination 1 Alex Benton, University of Cambridge A.Benton@damtp.cam.ac.uk Supported in part by Google UK, Ltd What s wrong with raytracing? Soft shadows are expensive Shadows
More informationINFOGR Computer Graphics. J. Bikker - April-July Lecture 10: Shading Models. Welcome!
INFOGR Computer Graphics J. Bikker - April-July 2016 - Lecture 10: Shading Models Welcome! Today s Agenda: Introduction Light Transport Materials Sensors Shading INFOGR Lecture 10 Shading Models 3 Introduction
More informationStatistical Acceleration for Animated Global Illumination
Statistical Acceleration for Animated Global Illumination Mark Meyer John Anderson Pixar Animation Studios Unfiltered Noisy Indirect Illumination Statistically Filtered Final Comped Frame Figure 1: An
More informationMonte Carlo Path Tracing
Page 1 Monte Carlo Path Tracing Today Path tracing Random wals and Marov chains Eye vs. light ray tracing Bidirectional ray tracing Next Irradiance caching Photon mapping Light Path Sx (, x) 0 1 f ( x,
More informationOngoing Developments in Photon Mapping
Ongoing Developments in Photon Mapping Roland Schregle, Stephen Wittkopf Competence Centre Envelopes and Solar Energy (CC-EASE) 13th International RADIANCE Workshop 2014 London, UK Outline 1. Introduction
More informationRendering Light Reflection Models
Rendering Light Reflection Models Visual Imaging in the Electronic Age Donald P. Greenberg October 3, 2017 Lecture #13 Program of Computer Graphics, Cornell University General Electric - 167 Cornell in
More informationGlobal Illumination The Game of Light Transport. Jian Huang
Global Illumination The Game of Light Transport Jian Huang Looking Back Ray-tracing and radiosity both computes global illumination Is there a more general methodology? It s a game of light transport.
More informationPaths, diffuse interreflections, caching and radiometry. D.A. Forsyth
Paths, diffuse interreflections, caching and radiometry D.A. Forsyth How we got here We want to render diffuse interreflections strategy: compute approximation B-hat, then gather B = E +(ρk)e +(ρk)( ˆB
More informationSOME THEORY BEHIND REAL-TIME RENDERING
SOME THEORY BEHIND REAL-TIME RENDERING Jaroslav Křivánek Charles University in Prague Off-line realistic rendering (not yet in rea-time) Ray tracing 3 4 Image created by Bertrand Benoit Rendered in Corona
More informationA NEW APPROACH OF DENSITY ESTIMATION FOR GLOBAL ILLUMINATION
A NEW APPROACH OF DENSITY ESTIMATION FOR GLOBAL ILLUMINATION Fabien Lavignotte, Mathias Paulin IRIT Université Paul Sabatier 8, route de Narbonne, 306 Toulouse cedex Toulouse, France e-mail : {lavignot,
More informationrendering equation computer graphics rendering equation 2009 fabio pellacini 1
rendering equation computer graphics rendering equation 2009 fabio pellacini 1 phsicall-based rendering snthesis algorithms that compute images b simulation the phsical behavior of light computer graphics
More informationGreg Ward / SIGGRAPH 2003
Global Illumination Global Illumination & HDRI Formats Greg Ward Anyhere Software Accounts for most (if not all) visible light interactions Goal may be to maximize realism, but more often visual reproduction
More informationChapter 11. Caustics and Global Illumination
11 and Global Illumination Chapter 11 Direct illumination occurs when a light source directly illuminates an object or objects in a scene. Indirect illumination occurs if light illuminates objects by reflection
More informationPhoton Mapping. Photon Mapping. Why Map Photons? Sources. What is a Photon? Refrac=on of a Caus=c. Jan Kautz
Refrac=on of a Caus=c Photon Mapping Jan Kautz Monte Carlo ray tracing handles all paths of light: L(D S)*E, but not equally well Has difficulty sampling LS*DS*E paths, e.g. refrac=on of a caus=c Path
More informationAnti-aliasing. Images and Aliasing
CS 130 Anti-aliasing Images and Aliasing Aliasing errors caused by rasterizing How to correct them, in general 2 1 Aliased Lines Stair stepping and jaggies 3 Remove the jaggies Anti-aliased Lines 4 2 Aliasing
More informationRadiometry, Radiosity and Photon Mapping
Radiometry, Radiosity and Photon Mapping When images produced using the rendering techniques described in Chapter 3 just are not giving you the realism you require probably the first technique that comes
More informationToday. Participating media. Participating media. Rendering Algorithms: Participating Media and. Subsurface scattering
Today Rendering Algorithms: Participating Media and Subsurface Scattering Introduction Rendering participating media Rendering subsurface scattering Spring 2009 Matthias Zwicker Participating media Participating
More informationPhoto Studio Optimizer
CATIA V5 Training Foils Photo Studio Optimizer Version 5 Release 19 September 008 EDU_CAT_EN_PSO_FF_V5R19 Photo Studio Optimizer Objectives of the course Upon completion of this course you will be able
More informationIntroduction to Radiosity
Introduction to Radiosity Produce photorealistic pictures using global illumination Mathematical basis from the theory of heat transfer Enables color bleeding Provides view independent representation Unfortunately,
More informationRealistic Image Synthesis
Realistic Image Synthesis Bidirectional Path Tracing & Reciprocity Karol Myszkowski Gurprit Singh Path Sampling Techniques Different techniques of sampling paths from both sides Numbers in parenthesis
More informationMonte Carlo Integration COS 323
Monte Carlo Integration COS 323 Integration in d Dimensions? One option: nested 1-D integration f(x,y) g(y) y f ( x, y) dx dy ( ) = g y dy x Evaluate the latter numerically, but each sample of g(y) is
More informationCENG 477 Introduction to Computer Graphics. Ray Tracing: Shading
CENG 477 Introduction to Computer Graphics Ray Tracing: Shading Last Week Until now we learned: How to create the primary rays from the given camera and image plane parameters How to intersect these rays
More informationA Survey of Radiosity and Ray-tracing. Methods in Global Illumination
A Survey of Radiosity and Ray-tracing Methods in Global Illumination Submitted by Ge Jin 12 th Dec 2000 To Dr. James Hahn Final Project of CS368 Advanced Topics in Computer Graphics Contents Abstract...3
More informationThe Rendering Equation & Monte Carlo Ray Tracing
Last Time? Local Illumination & Monte Carlo Ray Tracing BRDF Ideal Diffuse Reflectance Ideal Specular Reflectance The Phong Model Radiosity Equation/Matrix Calculating the Form Factors Aj Ai Reading for
More informationCS770/870 Spring 2017 Radiosity
CS770/870 Spring 2017 Radiosity Greenberg, SIGGRAPH 86 Tutorial Spencer, SIGGRAPH 93 Slide Set, siggraph.org/education/materials/hypergraph/radiosity/radiosity.htm Watt, 3D Computer Graphics -- Third Edition,
More informationGAMES Webinar: Rendering Tutorial 2. Monte Carlo Methods. Shuang Zhao
GAMES Webinar: Rendering Tutorial 2 Monte Carlo Methods Shuang Zhao Assistant Professor Computer Science Department University of California, Irvine GAMES Webinar Shuang Zhao 1 Outline 1. Monte Carlo integration
More informationGlobal Illumination. COMP 575/770 Spring 2013
Global Illumination COMP 575/770 Spring 2013 Final Exam and Projects COMP 575 Final Exam Friday, May 3 4:00 pm COMP 770 (and 575 extra credit) Projects Final report due by end of day, May 1 Presentations:
More informationComputer Graphics. Lecture 14 Bump-mapping, Global Illumination (1)
Computer Graphics Lecture 14 Bump-mapping, Global Illumination (1) Today - Bump mapping - Displacement mapping - Global Illumination Radiosity Bump Mapping - A method to increase the realism of 3D objects
More informationCS-184: Computer Graphics. Today. Lecture 22: Radiometry! James O Brien University of California, Berkeley! V2014-S
CS-184: Computer Graphics Lecture 22: Radiometry James O Brien University of California, Berkeley V2014-S-15-1.0 Today Radiometry: measuring light Local Illumination and Raytracing were discussed in an
More informationBioluminescence Chris Fontas & Forrest Browning
Bioluminescence Chris Fontas & Forrest Browning Introduction Our goal for the final project was to render a bioluminescent organism. Bioluminescence is a type of luminescence (cold light) resulting from
More informationSurface Integrators. Digital Image Synthesis Yung-Yu Chuang 12/13/2005
Surface Integrators Digital Image Synthesis Yung-Yu Chuang 12/13/2005 with slides by Pat Hanrahan, Henrik Jensen, Mario Costa Sousa and Torsten Moller Surface integrators Responsible for evaluating the
More informationRadiometry and reflectance
Radiometry and reflectance http://graphics.cs.cmu.edu/courses/15-463 15-463, 15-663, 15-862 Computational Photography Fall 2018, Lecture 16 Course announcements Homework 4 is still ongoing - Any questions?
More information