Global Illumination and Radiosity
|
|
- Buck Blankenship
- 6 years ago
- Views:
Transcription
1 Global Illumnaton and Radosty CS535 Danel G. Alaga Department of Computer Scence Purdue Unversty
2 Recall: Lghtng and Shadng Lght sources Pont lght Models an omndrectonal lght source (e.g., a bulb) Drectonal lght Models an omndrectonal lght source at nfnty Spot lght Models a pont lght wth drecton Lght model Ambent lght Dffuse reflecton Specular reflecton
3 Recall: Lghtng and Shadng Dffuse reflecton Lambertan model
4 Recall: Lghtng and Shadng Specular reflecton Phong model
5 Recall: Lghtng and Shadng Well.there s much more
6 For example Reflecton -> Bdrectonal Reflectance Dstrbuton Functons (BRDF) Dffuse, Specular -> Dffuse Interreflecton, Specular Interreflecton Color bleedng Transparency, Refracton Scatterng Subsurface scatterng Through partcpatng meda And more!
7 Illumnaton Models So far, you consdered mostly local (drect) llumnaton Lght drectly from lght sources to surface No shadows (actually s a global effect) Global (ndrect) llumnaton: multple bounces of lght Hard and soft shadows Reflectons/refractons (you knda saw already) Dffuse and specular nterreflectons
8 Welcome to Global Illumnaton Drect llumnaton + ndrect llumnaton; e.g. Drect = reflectons, refractons, shadows, Indrect = dffuse and specular nter-reflecton, wth global llumnaton only dffuse nter-reflecton drect llumnaton
9 Global Illumnaton Drect llumnaton + ndrect llumnaton; e.g. Drect = reflectons, refractons, shadows, Indrect = dffuse and specular nter-reflecton,
10 Reflectance Equaton x r L ( x, ) L ( x, ) L ( x, ) f ( x,, )( n) r r e r r Reflected Lght Emsson Incdent BRDF Cosne of (Output Image) Lght (from Incdent angle [Sldes wth help from Pat Hanrahan and Henrk Jensen] lght source)
11 Reflectance Equaton x r Sum over all lght sources L ( x, ) L ( x, ) L ( x, ) f ( x,, )( n) r r e r r Reflected Lght Emsson Incdent BRDF (Output Image) Lght (from lght source) Cosne of Incdent angle
12 Reflectance Equaton d x r L ( x, ) L ( x, ) L ( x, ) f( x,, ) cos d r r e r r Reflected Lght (Output Image) Emsson Replace sum wth ntegral Incdent Lght (from lght source) BRDF Cosne of Incdent angle
13 Reflectance Equaton d x r L ( x, ) L ( x, ) L ( x, ) f( x,, ) cos d r r e r r
14 The Challenge L ( x, ) L ( x, ) L ( x, ) f ( x,, ) cos d r r e r r Computng reflectance equaton requres knowng the ncomng radance from surfaces But determnng ncomng radance requres knowng the reflected radance from surfaces
15 Surfaces (nterreflecton) x da Global Illumnaton d x r Lr ( x, r ) Le ( x, r ) Lr ( x, ) f ( x,, r ) cosd Reflected Lght (Output Image) Emsson Reflected Lght (from prev surface) BRDF Cosne of Incdent angle
16 Renderng Equaton Surfaces (nterreflecton) x da d x r Lr ( x, r ) Le ( x, r ) Lr ( x, ) f ( x,, r ) cosd Reflected Lght (Output Image) UNKNOWN Emsson Reflected BRDF Cosne of Lght Incdent angle KNOWN UNKNOWN KNOWN KNOWN
17 Renderng Equaton (Kajya 1986)
18 Renderng Equaton as Integral Equaton Lr ( x, r ) Le ( x, r ) Lr ( x, ) f ( x,, r ) cosd Reflected Lght (Output Image) UNKNOWN Emsson Reflected BRDF Cosne of Lght Incdent angle KNOWN UNKNOWN KNOWN KNOWN Is a Fredholm Integral Equaton of second knd [extensvely studed numercally] wth canoncal form lu ( ) e( u) lv ( ) K( u, v ) dv Kernel of equaton
19 Lnear Operator Equaton lu ( ) e( u) lv ( ) K( u, v ) dv Kernel of equaton L EKL whch s effectvely a smple matrx equaton (or system of smultaneous lnear equatons) where L, E are vectors, K s the lght transport matrx (more on ths later!)
20 Solvng the Renderng Equaton (=how to compute L?) In general, too hard for analytc soluton But there are approxmatons and some nce observatons
21 Solvng the Renderng Equaton (=how to compute L?) L EKL IL KL E ( I K) L E L ( I K) 1 E (usng Bnomal Theorem) 2 3 L ( I K K K...) E 2 3 L E KE K E K E... where term n corresponds to n-th bounces of lght
22 Ray Tracng 2 3 L E KE K E K E... Emsson drectly From lght sources Drect Illumnaton on surfaces Global Illumnaton (One bounce ndrect) [Mrrors, Refracton] (Two bounce ndrect) [Caustcs, etc ]
23 Ray Tracng 2 3 L E KE KEKE... Emsson drectly From lght sources OpenGL Shadng Drect Illumnaton on surfaces Global Illumnaton (One bounce ndrect) [Mrrors, Refracton] (Two bounce ndrect) [Caustcs, etc ]
24
25 Radosty Radosty, nspred by deas from heat transfer, s an applcaton of a fnte element method to solvng the renderng equaton for scenes wth purely dffuse surfaces (renderng equaton) [Radosty sldes heavly based on Dr. Maro Costa Sousa, Dept. of of CS, U. Of Calgary]
26 Radosty Calculatng the overall lght propagaton wthn a scene, for short global llumnaton s a very dffcult problem. Wth a standard ray tracng algorthm, ths s a very tme consumng task, snce a huge number of rays have to be shot.
27 Radosty For ths reason, the radosty method was nvented. The man dea of the method s to store llumnaton values on the surfaces of the objects, as the lght s propagated startng at the lght sources.
28 Equaton: Radosty
29 Ray Tracng
30 Radosty
31 Dffuse Interreflecton (radosty method)
32 Radosty (Thermal Heat Transfer) The "radosty" method has ts bass n the feld of thermal heat transfer. Heat transfer theory descrbes radaton as the transfer of energy from a surface when that surface has been thermally excted.
33 Radosty (Computer Graphcs) Assumpton #1: surfaces are dffuse emtters and reflectors of energy, emttng and reflectng energy unformly over ther entre area. Assumpton #2: an equlbrum soluton can be reached; that all of the energy n an envronment s accounted for, through absorpton and reflecton. Also vewpont ndependent: the soluton wll be the same regardless of the vewpont of the mage.
34 The Radosty Equaton The "radosty equaton" descrbes the amount of energy whch can be emtted from a surface, as the sum of the energy nherent n the surface (a lght source, for example) and the energy whch strkes the surface, beng emtted from some other surface. The energy whch leaves a surface (surface "j") and strkes another surface (surface "") s attenuated by two factors: the "form factor" between surfaces "" and "j", whch accounts for the physcal relatonshp between the two surfaces the reflectvty of surface ", whch wll absorb a certan percentage of lght energy whch strkes the surface.
35 The Radosty Equaton B E B j F j Radosty of surface Emssvty of surface Radosty of surface j Form Factor of surface j relatve to surface Reflectvty of surface wll absorb a certan percentage of lght energy whch strkes the surface Surface Surface j accounts for the physcal relatonshp between the two surfaces
36 The Radosty Equaton B E B j F j Energy emtted by surface Surface j Surface
37 The Radosty Equaton B E B j F j Energy reachng surface from other surfaces Surface j Surface
38 The Radosty Equaton B E B j F j Energy reflected by surface Surface j Surface
39 Classc Radosty Algorthm Mesh Surfaces nto Elements Compute Form Factors Between Elements Solve Lnear System for Radostes Reconstruct and Dsplay Soluton
40 Classc Radosty Algorthm Mesh Surfaces nto Elements Compute Form Factors Between Elements Solve Lnear System for Radostes Reconstruct and Dsplay Soluton
41 The Form Factor: The fracton of energy leavng one surface that reaches another surface It s a purely geometrc relatonshp, ndependent of vewpont or surface attrbutes Surface j Surface
42 Between dfferental areas, the form factor equals: dfferental area of surface, j angle between Normal and r angle between Normal j and r FdA da j cos cos r 2 j Surface j j da j r vector from da to da j da Surface
43 Between dfferental areas, the form factor equals: The overall form factor between and j s found by ntegratng FdA da j j cos cos r 2 j F j 1 A 2 A A j cos cos r j da da j Surface j j da j r da Surface
44 Next Step: Learn ways of computng form factors Recall the Radosty Equaton: B E B j F j The F j are the form factors Form factors ndependent of radostes (depend only on scene geometry)
45 Form Factors n (More) Detal F j 1 2 A A A j cos cos r j da da j F j 1 A 2 A A j cos cos r j V j da da j where V j s the vsblty (0 or 1)
46 Form Factors n (More) Detal Several ways to fnd form factors Hemcube was orgnal method + Hardware acceleraton + Gves F daaj for all j n one pass - Alasng Area samplng methods now preferred Slower than hemcube but GPU-able As accurate as desred snce adaptve
47 Area Samplng Subdvde A j nto small peces da j For all da j cast ray daj-daj to determne V j f vsble compute F dadaj cos cos j FdAdA V j 2 r sum up F daaj += F dadaj j da j da ray da j A j We have now F daaj
48 Next We have the form factors How do we fnd the radosty soluton for the scene? The "Full Matrx" Radosty Algorthm Gatherng & Shootng Progressve Radosty Meshng
49 Radosty Matrx n j j j B F E B 1 n n nn n n n n n n n E E E B B B F F F F F F F F F n j j j E B F B 1 E B
50 Radosty Matrx The "full matrx" radosty soluton calculates the form factors between each par of surfaces n the envronment, then forms a seres of smultaneous lnear equatons. Ths matrx equaton s solved for the "B" values, whch can be used as the fnal ntensty (or color) value of each surface. n n nn n n n n n n n E E E B B B F F F F F F F F F
51 Radosty Matrx Ths method produces a complete soluton, at the substantal cost of frst calculatng form factors between each par of surfaces and then the soluton of the matrx equaton. Ths leads to substantal costs not only n computaton tme but n storage.
52 Next We have the form factors How do we fnd the radosty soluton for the scene? The "Full Matrx" Radosty Algorthm Gatherng & Shootng Progressve Radosty Meshng
53 Drect methods: O(n 3 ) Solve [F][B] = [E] Gaussan elmnaton Goral, Torrance, Greenberg, Battale, 1984 Iteratve methods: O(n 2 ) Energy conservaton dagonally domnant teraton converges Gauss-Sedel, Jacob: Gatherng Nshta, Nakamae, 1985 Cohen, Greenberg, 1985 Southwell: Shootng Cohen, Chen, Wallace, Greenberg, 1988
54 Gatherng In a sense, the lght leavng patch s determned by gatherng n the lght from the rest of the envronment B B due E to B j n j1 B j F B j j F j B E n Fj j1 B j
55 Gatherng Gatherng lght through a hem-cube allows one patch radosty to be updated. B E n Fj j1 B j
56 Gatherng
57 Successve Approxmaton
58 Shootng Shootng lght through a sngle hem-cube allows the whole envronment's radosty values to be updated smultaneously. For all j B j B j B E j j where F j F j A A j
59 Shootng
60 Progressve Radosty
61 Next We have the form factors How do we fnd the radosty soluton for the scene? The "Full Matrx" Radosty Algorthm Gatherng & Shootng Progressve Radosty Meshng
62 Accuracy
63 Artfacts
64 Increasng Resoluton
65 Adaptve Meshng
66 Some Radosty Results
67 The Cornell Box Ths s the orgnal Cornell box, as smulated by Cndy M. Goral, Kenneth E. Torrance, and Donald P. Greenberg for the 1984 paper Modelng the nteracton of Lght Between Dffuse Surfaces, Computer Graphcs (SIGGRAPH '84 Proceedngs), Vol. 18, No. 3, July 1984, pp Because form factors were computed analytcally, no occludng objects were ncluded nsde the box.
68 The Cornell Box Ths smulaton of the Cornell box was done by Mchael F. Cohen and Donald P. Greenberg for the 1985 paper The Hem-Cube, A Radosty Soluton for Complex Envronments, Vol. 19, No. 3, July 1985, pp The hem-cube allowed form factors to be calculated usng scan converson algorthms (whch were avalable n hardware), and made t possble to calculate shadows from occludng objects.
69
70
71
72
73 Dscontnuty Meshng Dan Lschnsk, Flppo Tamper and Donald P. Greenberg created ths mage for the 1992 paper Dscontnuty Meshng for Accurate Radosty. It depcts a scene that represents a pathologcal case for tradtonal radosty mages, many small shadow castng detals. Notce, n partcular, the shadows cast by the wndows, and the slats n the char.
74
75 Opera Lghtng Ths scene from La Boheme demonstrates the use of focused lghtng and angular projecton of predstorted mages for the background. It was rendered by Jule O'B. Dorsey, Francos X. Sllon, and Donald P. Greenberg for the 1991 paper Desgn and Smulaton of Opera Lghtng and Projecton Effects.
76
77 Radosty Factory These two mages were rendered by Mchael F. Cohen, Shenchang Erc Chen, John R. Wallace and Donald P. Greenberg for the 1988 paper A Progressve Refnement Approach to Fast Radosty Image Generaton. The factory model contans 30,000 patches, and was the most complex radosty soluton computed at that tme. The radosty soluton took approxmately 5 hours for 2,000 shots, and the mage generaton requred 190 hours; each on a VAX8700.
78
79 Museum Most of the llumnaton that comes nto ths smulated museum arrves va the baffles on the celng. As the progressve radosty soluton executed, users could wtness each of the baffles beng llumnated from above, and then reflectng some of ths lght to the bottom of an adjacent baffle. A porton of ths reflected lght was eventually bounced down nto the room. The mage appeared on the proceedngs cover of SIGGRAPH 1988.
80
81
82
83
84
85
86
Global Illumination and Radiosity
Global Illumnaton and Radosty CS535 Danel G. Alaga Department of Computer Scence Purdue Unversty Recall: Lghtng and Shadng Lght sources Pont lght Models an omndrectonal lght source (e.g., a bulb) Drectonal
More informationGlobal Illumination and Radiosity
Global Illumnaton and Radosty CS535 Danel lg. Alaga Department of Computer Scence Purdue Unversty Recall: Lghtng and Shadng Lght sources Pont lght Models an omndrectonal lght source (e.g., a bulb) Drectonal
More informationGlobal Illumination: Radiosity
Last Tme? Global Illumnaton: Radosty Planar Shadows Shadow Maps An early applcaton of radatve heat transfer n stables. Projectve Texture Shadows (Texture Mappng) Shadow Volumes (Stencl Buffer) Schedule
More informationGlobal Illumination and Radiosity
Global Illumination and Radiosity CS434 Daniel G. Aliaga Department of Computer Science Purdue University Recall: Lighting and Shading Light sources Point light Models an omnidirectional light source (e.g.,
More informationComputer Graphics. Jeng-Sheng Yeh 葉正聖 Ming Chuan University (modified from Bing-Yu Chen s slides)
Computer Graphcs Jeng-Sheng Yeh 葉正聖 Mng Chuan Unversty (modfed from Bng-Yu Chen s sldes) llumnaton and Shadng llumnaton Models Shadng Models for Polygons Surface Detal Shadows Transparency Global llumnaton
More informationDiscussion. History and Outline. Smoothness of Indirect Lighting. Irradiance Caching. Irradiance Calculation. Advanced Computer Graphics (Fall 2009)
Advanced Computer Graphcs (Fall 2009 CS 29, Renderng Lecture 6: Recent Advances n Monte Carlo Offlne Renderng Rav Ramamoorth http://nst.eecs.berkeley.edu/~cs29-13/fa09 Dscusson Problems dfferent over years.
More informationReal-time. Shading of Folded Surfaces
Rhensche Fredrch-Wlhelms-Unverstät Bonn Insttute of Computer Scence II Computer Graphcs Real-tme Shadng of Folded Surfaces B. Ganster, R. Klen, M. Sattler, R. Sarlette Motvaton http://www www.vrtualtryon.de
More informationDiscussion. History and Outline. Smoothness of Indirect Lighting. Irradiance Calculation. Irradiance Caching. Advanced Computer Graphics (Fall 2009)
Advanced Computer Graphcs (Fall 2009 CS 283, Lecture 13: Recent Advances n Monte Carlo Offlne Renderng Rav Ramamoorth http://nst.eecs.berkeley.edu/~cs283/fa10 Dscusson Problems dfferent over years. Intally,
More informationIntroduction to Radiosity
EECS 487: Interactve Computer Graphcs EECS 487: Interactve Computer Graphcs Renderng a Scene Introducton to Radosty John. Hughes and ndres van Dam rown Unversty The scene conssts of a geometrc arrangement
More informationGlobal Illumination. Computer Graphics COMP 770 (236) Spring Instructor: Brandon Lloyd 3/26/07 1
Global Illumnaton Computer Graphcs COMP 770 (236) Sprng 2007 Instructor: Brandon Lloyd 3/26/07 1 From last tme Robustness ssues Code structure Optmzatons Acceleraton structures Dstrbuton ray tracng ant-alasng
More informationColor in OpenGL Polygonal Shading Light Source in OpenGL Material Properties Normal Vectors Phong model
Color n OpenGL Polygonal Shadng Lght Source n OpenGL Materal Propertes Normal Vectors Phong model 2 We know how to rasterze - Gven a 3D trangle and a 3D vewpont, we know whch pxels represent the trangle
More informationMonte Carlo Rendering
Monte Carlo Renderng Last Tme? Modern Graphcs Hardware Cg Programmng Language Gouraud Shadng vs. Phong Normal Interpolaton Bump, Dsplacement, & Envronment Mappng Cg Examples G P R T F P D Today Does Ray
More informationScan Conversion & Shading
Scan Converson & Shadng Thomas Funkhouser Prnceton Unversty C0S 426, Fall 1999 3D Renderng Ppelne (for drect llumnaton) 3D Prmtves 3D Modelng Coordnates Modelng Transformaton 3D World Coordnates Lghtng
More informationScan Conversion & Shading
1 3D Renderng Ppelne (for drect llumnaton) 2 Scan Converson & Shadng Adam Fnkelsten Prnceton Unversty C0S 426, Fall 2001 3DPrmtves 3D Modelng Coordnates Modelng Transformaton 3D World Coordnates Lghtng
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 informationDiffuse and specular interreflections with classical, deterministic ray tracing
Dffuse and specular nterreflectons wth classcal, determnstc ray tracng Gergely Vass gergely_vass@sggraph.org Dept. of Control Engneerng and Informaton Technology Techncal Unversty of Budapest Budapest,
More informationSurface Mapping One. CS7GV3 Real-time Rendering
Surface Mappng One CS7GV3 Real-tme Renderng Textures Add complexty to scenes wthout addtonal geometry Textures store ths nformaton, can be any dmenson Many dfferent types: Dffuse most common Ambent, specular,
More informationForm-factors Josef Pelikán CGG MFF UK Praha.
Form-factors 1996-2016 Josef Pelkán CGG MFF UK Praha pepca@cgg.mff.cun.cz http://cgg.mff.cun.cz/~pepca/ FormFactor 2016 Josef Pelkán, http://cgg.mff.cun.cz/~pepca 1 / 23 Form-factor F It ndcates the proporton
More informationComparison of calculation methods and models in software for computer graphics and radiative heat exchange
Comparson of calculaton methods and models n software for computer graphcs and radatve heat exchange Insttute of Electrcal and Electroncs Engneerng Poznan Unversty of Technology ul. Potrowo 3A, 60-950
More informationPlane Sampling for Light Paths from the Environment Map
jgt 2009/5/27 16:42 page 1 #1 Vol. [VOL], No. [ISS]: 1 6 Plane Samplng for Lght Paths from the Envronment Map Holger Dammertz and Johannes Hanka Ulm Unversty Abstract. We present a method to start lght
More informationConsistent Illumination within Optical See-Through Augmented Environments
Consstent Illumnaton wthn Optcal See-Through Augmented Envronments Olver Bmber, Anselm Grundhöfer, Gordon Wetzsten and Sebastan Knödel Bauhaus Unversty Bauhausstraße 11, 99423 Wemar, Germany, {olver.bmber,
More informationSurface Integrators. Digital Image Synthesis Yung-Yu Chuang 12/20/2007
Surface Integrators Dgtal Image Synthess Yung-Yu Chuang 12/20/2007 wth sldes by Peter Shrley, Pat Hanrahan, Henrk Jensen, Maro Costa Sousa and Torsten Moller Drect lghtng va Monte Carlo ntegraton dffuse
More informationPhysics 132 4/24/17. April 24, 2017 Physics 132 Prof. E. F. Redish. Outline
Aprl 24, 2017 Physcs 132 Prof. E. F. Redsh Theme Musc: Justn Tmberlake Mrrors Cartoon: Gary Larson The Far Sde 1 Outlne Images produced by a curved mrror Image equatons for a curved mrror Lght n dense
More informationMonte Carlo 1: Integration
Monte Carlo : Integraton Prevous lecture: Analytcal llumnaton formula Ths lecture: Monte Carlo Integraton Revew random varables and probablty Samplng from dstrbutons Samplng from shapes Numercal calculaton
More informationSome Tutorial about the Project. Computer Graphics
Some Tutoral about the Project Lecture 6 Rastersaton, Antalasng, Texture Mappng, I have already covered all the topcs needed to fnsh the 1 st practcal Today, I wll brefly explan how to start workng on
More information2.2 Photometric Image Formation
2.2 Photometrc Image Formaton mage plane n source sensor plane optcs!1 Illumnaton Computer son ory s ten deeloped wth assumpton a pont source at nfnty. But een sun has a fnte extent (about 0.5 deg sual
More informationR s s f. m y s. SPH3UW Unit 7.3 Spherical Concave Mirrors Page 1 of 12. Notes
SPH3UW Unt 7.3 Sphercal Concave Mrrors Page 1 of 1 Notes Physcs Tool box Concave Mrror If the reflectng surface takes place on the nner surface of the sphercal shape so that the centre of the mrror bulges
More informationMonte Carlo 1: Integration
Monte Carlo : Integraton Prevous lecture: Analytcal llumnaton formula Ths lecture: Monte Carlo Integraton Revew random varables and probablty Samplng from dstrbutons Samplng from shapes Numercal calculaton
More informationFast, Arbitrary BRDF Shading for Low-Frequency Lighting Using Spherical Harmonics
Thrteenth Eurographcs Workshop on Renderng (2002) P. Debevec and S. Gbson (Edtors) Fast, Arbtrary BRDF Shadng for Low-Frequency Lghtng Usng Sphercal Harmoncs Jan Kautz 1, Peter-Pke Sloan 2 and John Snyder
More informationInteractive Rendering of Translucent Objects
Interactve Renderng of Translucent Objects Hendrk Lensch Mchael Goesele Phlppe Bekaert Jan Kautz Marcus Magnor Jochen Lang Hans-Peter Sedel 2003 Presented By: Mark Rubelmann Outlne Motvaton Background
More informationLighting. Dr. Scott Schaefer
Lghtng Dr. Scott Schaefer 1 Lghtng/Illumnaton Color s a functon of how lght reflects from surfaces to the eye Global llumnaton accounts for lght from all sources as t s transmtted throughout the envronment
More informationAn exhaustive error-bounding algorithm for hierarchical radiosity
An exhaustve error-boundng algorthm for herarchcal radosty Ncolas Holzschuch, Franços X. Sllon To cte ths verson: Ncolas Holzschuch, Franços X. Sllon. An exhaustve error-boundng algorthm for herarchcal
More informationSimplification of 3D Meshes
Smplfcaton of 3D Meshes Addy Ngan /4/00 Outlne Motvaton Taxonomy of smplfcaton methods Hoppe et al, Mesh optmzaton Hoppe, Progressve meshes Smplfcaton of 3D Meshes 1 Motvaton Hgh detaled meshes becomng
More informationRange images. Range image registration. Examples of sampling patterns. Range images and range surfaces
Range mages For many structured lght scanners, the range data forms a hghly regular pattern known as a range mage. he samplng pattern s determned by the specfc scanner. Range mage regstraton 1 Examples
More informationMotivation. Motivation. Monte Carlo. Example: Soft Shadows. Outline. Monte Carlo Algorithms. Advanced Computer Graphics (Fall 2009)
Advanced Comuter Grahcs Fall 29 CS 294, Renderng Lecture 4: Monte Carlo Integraton Rav Ramamoorth htt://nst.eecs.berkeley.edu/~cs294-3/a9 Motvaton Renderng = ntegraton Relectance equaton: Integrate over
More informationCluster Analysis of Electrical Behavior
Journal of Computer and Communcatons, 205, 3, 88-93 Publshed Onlne May 205 n ScRes. http://www.scrp.org/ournal/cc http://dx.do.org/0.4236/cc.205.350 Cluster Analyss of Electrcal Behavor Ln Lu Ln Lu, School
More informationComputer Sciences Department
Computer Scences Department Populaton Monte Carlo Path Tracng Yu-Ch La Charles Dyer Techncal Report #1614 September 2007 Populaton Monte Carlo Path Tracng Yu-Ch La Unversty of Wsconsn at Madson Graphcs-Vson
More information6.854 Advanced Algorithms Petar Maymounkov Problem Set 11 (November 23, 2005) With: Benjamin Rossman, Oren Weimann, and Pouya Kheradpour
6.854 Advanced Algorthms Petar Maymounkov Problem Set 11 (November 23, 2005) Wth: Benjamn Rossman, Oren Wemann, and Pouya Kheradpour Problem 1. We reduce vertex cover to MAX-SAT wth weghts, such that the
More informationObject Recognition Based on Photometric Alignment Using Random Sample Consensus
Vol. 44 No. SIG 9(CVIM 7) July 2003 3 attached shadow photometrc algnment RANSAC RANdom SAmple Consensus Yale Face Database B RANSAC Object Recognton Based on Photometrc Algnment Usng Random Sample Consensus
More informationElectrical analysis of light-weight, triangular weave reflector antennas
Electrcal analyss of lght-weght, trangular weave reflector antennas Knud Pontoppdan TICRA Laederstraede 34 DK-121 Copenhagen K Denmark Emal: kp@tcra.com INTRODUCTION The new lght-weght reflector antenna
More informationInteractive Virtual Relighting of Real Scenes
Frst submtted: October 1998 (#846). Edtor/revewers please consult accompanyng document wth detaled responses to revewer comments. Interactve Vrtual Relghtng of Real Scenes Célne Loscos, George Drettaks,
More informationKiran Joy, International Journal of Advanced Engineering Technology E-ISSN
Kran oy, nternatonal ournal of Advanced Engneerng Technology E-SS 0976-3945 nt Adv Engg Tech/Vol. V/ssue /Aprl-une,04/9-95 Research Paper DETERMATO O RADATVE VEW ACTOR WTOUT COSDERG TE SADOWG EECT Kran
More informationCompiler Design. Spring Register Allocation. Sample Exercises and Solutions. Prof. Pedro C. Diniz
Compler Desgn Sprng 2014 Regster Allocaton Sample Exercses and Solutons Prof. Pedro C. Dnz USC / Informaton Scences Insttute 4676 Admralty Way, Sute 1001 Marna del Rey, Calforna 90292 pedro@s.edu Regster
More informationGSLM Operations Research II Fall 13/14
GSLM 58 Operatons Research II Fall /4 6. Separable Programmng Consder a general NLP mn f(x) s.t. g j (x) b j j =. m. Defnton 6.. The NLP s a separable program f ts objectve functon and all constrants are
More informationSLAM Summer School 2006 Practical 2: SLAM using Monocular Vision
SLAM Summer School 2006 Practcal 2: SLAM usng Monocular Vson Javer Cvera, Unversty of Zaragoza Andrew J. Davson, Imperal College London J.M.M Montel, Unversty of Zaragoza. josemar@unzar.es, jcvera@unzar.es,
More informationExercises (Part 4) Introduction to R UCLA/CCPR. John Fox, February 2005
Exercses (Part 4) Introducton to R UCLA/CCPR John Fox, February 2005 1. A challengng problem: Iterated weghted least squares (IWLS) s a standard method of fttng generalzed lnear models to data. As descrbed
More informationComputer graphics III Light reflection, BRDF. Jaroslav Křivánek, MFF UK
Computer graphcs III Lght reflecton, BRDF Jaroslav Křvánek, MFF UK Jaroslav.Krvanek@mff.cun.cz Basc radometrc quanttes Image: Wojcech Jarosz CG III (NPGR010) - J. Křvánek 2015 Interacton of lght wth a
More informationWavefront Reconstructor
A Dstrbuted Smplex B-Splne Based Wavefront Reconstructor Coen de Vsser and Mchel Verhaegen 14-12-201212 2012 Delft Unversty of Technology Contents Introducton Wavefront reconstructon usng Smplex B-Splnes
More informationModeling, Manipulating, and Visualizing Continuous Volumetric Data: A Novel Spline-based Approach
Modelng, Manpulatng, and Vsualzng Contnuous Volumetrc Data: A Novel Splne-based Approach Jng Hua Center for Vsual Computng, Department of Computer Scence SUNY at Stony Brook Talk Outlne Introducton and
More informationRealistic Rendering. Traditional Computer Graphics. Traditional Computer Graphics. Production Pipeline. Appearance in the Real World
Advanced Computer Graphcs (Fall 2009 CS 294, Renderng Lecture 11 Representatons of Vsual Appearance Rav Ramamoorth Realstc Renderng Geometry Renderng Algorthm http://nst.eecs.berkeley.edu/~cs294-13/fa09
More informationAMath 483/583 Lecture 21 May 13, Notes: Notes: Jacobi iteration. Notes: Jacobi with OpenMP coarse grain
AMath 483/583 Lecture 21 May 13, 2011 Today: OpenMP and MPI versons of Jacob teraton Gauss-Sedel and SOR teratve methods Next week: More MPI Debuggng and totalvew GPU computng Read: Class notes and references
More informationS1 Note. Basis functions.
S1 Note. Bass functons. Contents Types of bass functons...1 The Fourer bass...2 B-splne bass...3 Power and type I error rates wth dfferent numbers of bass functons...4 Table S1. Smulaton results of type
More informationNUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS
ARPN Journal of Engneerng and Appled Scences 006-017 Asan Research Publshng Network (ARPN). All rghts reserved. NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS Igor Grgoryev, Svetlana
More informationRobust Soft Shadow Mapping with Backprojection and Depth Peeling
paper 2008/3/20 15:47 page 19 #1 Vol. 13, No. 1: 19 29 Robust Soft Shadow Mappng wth Backprojecton and Depth Peelng Lous Bavol, Steven P. Callahan, and Claudo T. Slva Scentfc Computng and Imagng Insttute,
More informationDIFFRACTION SHADING MODELS FOR IRIDESCENT SURFACES
DIFFRACTION SHADING MODELS FOR IRIDESCENT SURFACES Emmanuel Agu Department of Computer Scence Worcester Polytechnc Insttute, Worcester, MA 01609, USA emmanuel@cs.wp.edu Francs S.Hll Jr Department of Electrcal
More informationRobust Soft Shadow Mapping with Depth Peeling
1 Robust Soft Shadow Mappng wth Depth Peelng Lous Bavol, Steven P. Callahan, Cláudo T. Slva UUSCI-2006-028 Scentfc Computng and Imagng Insttute Unversty of Utah Salt Lake Cty, UT 84112 USA August 11, 2006
More informationAn Optimal Algorithm for Prufer Codes *
J. Software Engneerng & Applcatons, 2009, 2: 111-115 do:10.4236/jsea.2009.22016 Publshed Onlne July 2009 (www.scrp.org/journal/jsea) An Optmal Algorthm for Prufer Codes * Xaodong Wang 1, 2, Le Wang 3,
More informationMonte Carlo Integration
Introducton Monte Carlo Integraton Dgtal Image Synthess Yung-Yu Chuang 11/9/005 The ntegral equatons generally don t have analytc solutons, so we must turn to numercal methods. L ( o p,ωo) = L e ( p,ωo)
More informationTopic 13: Radiometry. The Basic Light Transport Path
Topc 3: Raometry The bg pcture Measurng lght comng from a lght source Measurng lght fallng onto a patch: Irraance Measurng lght leavng a patch: Raance The Lght Transport Cycle The BrecAonal Reflectance
More informationPBRT core. Announcements. pbrt. pbrt plug-ins
Announcements PBRT core Dgtal Image Synthess Yung-Yu Chuang 9/27/2007 Please subscrbe the malng lst. Wndows complaton Debuggng n Wndows Doxygen (onlne, download or doxygen by yourself) HW#1 wll be assgned
More informationLight Factorization for Mixed-Frequency Shadows in Augmented Reality
Lght Factorzaton for Mxed-Frequency Shadows n Augmented Realty Dere Nowrouzezahra 1 Stefan Geger 2 Kenny Mtchell 3 Robert Sumner 1 Wojcech Jarosz 1 Marus Gross 1,2 1 Dsney Research Zurch 2 ETH Zurch 3
More informationAngle-Independent 3D Reconstruction. Ji Zhang Mireille Boutin Daniel Aliaga
Angle-Independent 3D Reconstructon J Zhang Mrelle Boutn Danel Alaga Goal: Structure from Moton To reconstruct the 3D geometry of a scene from a set of pctures (e.g. a move of the scene pont reconstructon
More informationComplex Filtering and Integration via Sampling
Overvew Complex Flterng and Integraton va Samplng Sgnal processng Sample then flter (remove alases) then resample onunform samplng: jtterng and Posson dsk Statstcs Monte Carlo ntegraton and probablty theory
More informationShort Papers. Toward Accurate Recovery of Shape from Shading Under Diffuse Lighting 1 INTRODUCTION 2 PROBLEM FORMULATION
1020 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 19, NO. 9, SEPTEMBER 1997 Short Papers Toward Accurate Recovery of Shape from Shadng Under Dffuse Lghtng A. James Stewart and Mchael
More informationProblem Set 3 Solutions
Introducton to Algorthms October 4, 2002 Massachusetts Insttute of Technology 6046J/18410J Professors Erk Demane and Shaf Goldwasser Handout 14 Problem Set 3 Solutons (Exercses were not to be turned n,
More informationThe Shortest Path of Touring Lines given in the Plane
Send Orders for Reprnts to reprnts@benthamscence.ae 262 The Open Cybernetcs & Systemcs Journal, 2015, 9, 262-267 The Shortest Path of Tourng Lnes gven n the Plane Open Access Ljuan Wang 1,2, Dandan He
More informationProblem Definitions and Evaluation Criteria for Computational Expensive Optimization
Problem efntons and Evaluaton Crtera for Computatonal Expensve Optmzaton B. Lu 1, Q. Chen and Q. Zhang 3, J. J. Lang 4, P. N. Suganthan, B. Y. Qu 6 1 epartment of Computng, Glyndwr Unversty, UK Faclty
More informationAn Application of the Dulmage-Mendelsohn Decomposition to Sparse Null Space Bases of Full Row Rank Matrices
Internatonal Mathematcal Forum, Vol 7, 2012, no 52, 2549-2554 An Applcaton of the Dulmage-Mendelsohn Decomposton to Sparse Null Space Bases of Full Row Rank Matrces Mostafa Khorramzadeh Department of Mathematcal
More informationComputer Animation and Visualisation. Lecture 4. Rigging / Skinning
Computer Anmaton and Vsualsaton Lecture 4. Rggng / Sknnng Taku Komura Overvew Sknnng / Rggng Background knowledge Lnear Blendng How to decde weghts? Example-based Method Anatomcal models Sknnng Assume
More informationMathematics 256 a course in differential equations for engineering students
Mathematcs 56 a course n dfferental equatons for engneerng students Chapter 5. More effcent methods of numercal soluton Euler s method s qute neffcent. Because the error s essentally proportonal to the
More informationCircuit Analysis I (ENGR 2405) Chapter 3 Method of Analysis Nodal(KCL) and Mesh(KVL)
Crcut Analyss I (ENG 405) Chapter Method of Analyss Nodal(KCL) and Mesh(KVL) Nodal Analyss If nstead of focusng on the oltages of the crcut elements, one looks at the oltages at the nodes of the crcut,
More informationA Binarization Algorithm specialized on Document Images and Photos
A Bnarzaton Algorthm specalzed on Document mages and Photos Ergna Kavalleratou Dept. of nformaton and Communcaton Systems Engneerng Unversty of the Aegean kavalleratou@aegean.gr Abstract n ths paper, a
More informationLoop Transformations, Dependences, and Parallelization
Loop Transformatons, Dependences, and Parallelzaton Announcements Mdterm s Frday from 3-4:15 n ths room Today Semester long project Data dependence recap Parallelsm and storage tradeoff Scalar expanson
More informationFreeform Shading and Lighting Systems from Planar Quads
Freeform Shadng and Lghtng Systems from Planar Quads Cagu Jang, Jun Wang Kng Abdullah Unversty of Scence and Technology, Thuwal, Saud Araba Phllppe Bompas Archtect, 70 rue du Temple, Pars, France Helmut
More informationCollaboratively Regularized Nearest Points for Set Based Recognition
Academc Center for Computng and Meda Studes, Kyoto Unversty Collaboratvely Regularzed Nearest Ponts for Set Based Recognton Yang Wu, Mchhko Mnoh, Masayuk Mukunok Kyoto Unversty 9/1/013 BMVC 013 @ Brstol,
More informationComplex Numbers. Now we also saw that if a and b were both positive then ab = a b. For a second let s forget that restriction and do the following.
Complex Numbers The last topc n ths secton s not really related to most of what we ve done n ths chapter, although t s somewhat related to the radcals secton as we wll see. We also won t need the materal
More informationChapter 6 Programmng the fnte element method Inow turn to the man subject of ths book: The mplementaton of the fnte element algorthm n computer programs. In order to make my dscusson as straghtforward
More informationVery simple computational domains can be discretized using boundary-fitted structured meshes (also called grids)
Structured meshes Very smple computatonal domans can be dscretzed usng boundary-ftted structured meshes (also called grds) The grd lnes of a Cartesan mesh are parallel to one another Structured meshes
More informationSolving two-person zero-sum game by Matlab
Appled Mechancs and Materals Onlne: 2011-02-02 ISSN: 1662-7482, Vols. 50-51, pp 262-265 do:10.4028/www.scentfc.net/amm.50-51.262 2011 Trans Tech Publcatons, Swtzerland Solvng two-person zero-sum game by
More informationPHYS 219 Spring semester Lecture 20: Reflection of Electromagnetic Radiation: Mirrors and Images Formed by Mirrors
PHYS 219 Sprng semester 2014 Lecture 20: eflecton of Electromagnetc adaton: Mrrors and Images Formed by Mrrors on efenberger Brck Nanotechnology Center Purdue Unversty Lecture 20 1 evew: Snapshot of an
More informationCourse Introduction. Algorithm 8/31/2017. COSC 320 Advanced Data Structures and Algorithms. COSC 320 Advanced Data Structures and Algorithms
Course Introducton Course Topcs Exams, abs, Proects A quc loo at a few algorthms 1 Advanced Data Structures and Algorthms Descrpton: We are gong to dscuss algorthm complexty analyss, algorthm desgn technques
More informationSum of Linear and Fractional Multiobjective Programming Problem under Fuzzy Rules Constraints
Australan Journal of Basc and Appled Scences, 2(4): 1204-1208, 2008 ISSN 1991-8178 Sum of Lnear and Fractonal Multobjectve Programmng Problem under Fuzzy Rules Constrants 1 2 Sanjay Jan and Kalash Lachhwan
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 informationLecture 5: Multilayer Perceptrons
Lecture 5: Multlayer Perceptrons Roger Grosse 1 Introducton So far, we ve only talked about lnear models: lnear regresson and lnear bnary classfers. We noted that there are functons that can t be represented
More informationParallelism for Nested Loops with Non-uniform and Flow Dependences
Parallelsm for Nested Loops wth Non-unform and Flow Dependences Sam-Jn Jeong Dept. of Informaton & Communcaton Engneerng, Cheonan Unversty, 5, Anseo-dong, Cheonan, Chungnam, 330-80, Korea. seong@cheonan.ac.kr
More informationDetermining the Optimal Bandwidth Based on Multi-criterion Fusion
Proceedngs of 01 4th Internatonal Conference on Machne Learnng and Computng IPCSIT vol. 5 (01) (01) IACSIT Press, Sngapore Determnng the Optmal Bandwdth Based on Mult-crteron Fuson Ha-L Lang 1+, Xan-Mn
More informationSmooth Probabilistic Ambient Occlusion for Volume Rendering
Smooth Probablstc Ambent Occluson for Volume Renderng Thomas Kroes, Drk Schut, and Elmar Esemann 1.1 Introducton Ambent occluson [Zhukov et al. 98] s a compellng approach to mprove depth and shape percepton
More informationStochastic Rendering of Density Fields. Jos Stam. Department of Computer Science. University of Toronto.
Stochastc Renderng of Densty Felds Jos Stam Department of Computer Scence Unversty of Toronto stam@dgp.toronto.edu Abstract Stochastc models are often economcal to generate but problematc to render. Most
More informationFeature Reduction and Selection
Feature Reducton and Selecton Dr. Shuang LIANG School of Software Engneerng TongJ Unversty Fall, 2012 Today s Topcs Introducton Problems of Dmensonalty Feature Reducton Statstc methods Prncpal Components
More informationVirtual Memory. Background. No. 10. Virtual Memory: concept. Logical Memory Space (review) Demand Paging(1) Virtual Memory
Background EECS. Operatng System Fundamentals No. Vrtual Memory Prof. Hu Jang Department of Electrcal Engneerng and Computer Scence, York Unversty Memory-management methods normally requres the entre process
More informationS.P.H. : A SOLUTION TO AVOID USING EROSION CRITERION?
S.P.H. : A SOLUTION TO AVOID USING EROSION CRITERION? Célne GALLET ENSICA 1 place Emle Bloun 31056 TOULOUSE CEDEX e-mal :cgallet@ensca.fr Jean Luc LACOME DYNALIS Immeuble AEROPOLE - Bat 1 5, Avenue Albert
More informationDynamic Simulation of Optical MEM Switches
Dynamc Smulaton of Optcal MEM Swtches Tmothy P. Kurzweg, Jose A. Martnez, Steven P. Levtan Department of Electrcal Engneerng, Unversty of Pttsburgh, 348 Benedum Hall, Pttsburgh, PA 15261 tm@ee.ptt.edu,
More informationProgramming in Fortran 90 : 2017/2018
Programmng n Fortran 90 : 2017/2018 Programmng n Fortran 90 : 2017/2018 Exercse 1 : Evaluaton of functon dependng on nput Wrte a program who evaluate the functon f (x,y) for any two user specfed values
More informationHigh-Boost Mesh Filtering for 3-D Shape Enhancement
Hgh-Boost Mesh Flterng for 3-D Shape Enhancement Hrokazu Yagou Λ Alexander Belyaev y Damng We z Λ y z ; ; Shape Modelng Laboratory, Unversty of Azu, Azu-Wakamatsu 965-8580 Japan y Computer Graphcs Group,
More informationInverse Kinematics (part 2) CSE169: Computer Animation Instructor: Steve Rotenberg UCSD, Spring 2016
Inverse Knematcs (part 2) CSE169: Computer Anmaton Instructor: Steve Rotenberg UCSD, Sprng 2016 Forward Knematcs We wll use the vector: Φ... 1 2 M to represent the array of M jont DOF values We wll also
More informationRendering of Complex Materials for Driving Simulators
Renderng of Complex Materals for Drvng Smulators Therry Lefebvre 1,2 +33 (0)1.76.85.06.64 therry.t.lefebvre@renault.com Andras Kemeny 1 +33 (0)1.76.85.19.85 andras.kemeny@renault.com Dder Arquès 2 +33
More informationTN348: Openlab Module - Colocalization
TN348: Openlab Module - Colocalzaton Topc The Colocalzaton module provdes the faclty to vsualze and quantfy colocalzaton between pars of mages. The Colocalzaton wndow contans a prevew of the two mages
More informationModel-Based Bundle Adjustment to Face Modeling
Model-Based Bundle Adjustment to Face Modelng Oscar K. Au Ivor W. sang Shrley Y. Wong oscarau@cs.ust.hk vor@cs.ust.hk shrleyw@cs.ust.hk he Hong Kong Unversty of Scence and echnology Realstc facal synthess
More informationA Range Image Refinement Technique for Multi-view 3D Model Reconstruction
A Range Image Refnement Technque for Mult-vew 3D Model Reconstructon Soon-Yong Park and Mural Subbarao Electrcal and Computer Engneerng State Unversty of New York at Stony Brook, USA E-mal: parksy@ece.sunysb.edu
More informationFast Computation of Shortest Path for Visiting Segments in the Plane
Send Orders for Reprnts to reprnts@benthamscence.ae 4 The Open Cybernetcs & Systemcs Journal, 04, 8, 4-9 Open Access Fast Computaton of Shortest Path for Vstng Segments n the Plane Ljuan Wang,, Bo Jang
More information