18. Radiosity
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Path Tracing
Path Tracing Steve Rotenberg CSE168: Rendering Algorithms UCSD, Spring 2017 Irradiance Circumference of a Circle • The circumference of a circle of radius r is 2πr • In fact, a radian is defined as the angle you get on an arc of length r • We can represent the circumference of a circle as an integral 2휋 푐푖푟푐 = 푟푑휑 0 • This is essentially computing the length of the circumference as an infinite sum of infinitesimal segments of length 푟푑휑, over the range from 휑=0 to 2π Area of a Hemisphere • We can compute the area of a hemisphere by integrating ‘rings’ ranging over a second angle 휃, which ranges from 0 (at the north pole) to π/2 (at the equator) • The area of a ring is the circumference of the ring times the width 푟푑휃 • The circumference is going to be scaled by sin휃 as the rings are smaller towards the top of the hemisphere 휋 2 2휋 2 2 푎푟푒푎 = sin 휃 푟 푑휑 푑휃 = 2휋푟 0 0 Hemisphere Integral 휋 2 2휋 2 푎푟푒푎 = sin 휃 푟 푑휑 푑휃 0 0 • We are effectively computing an infinite summation of tiny rectangular area elements over a two dimensional domain. Each element has dimensions: sin 휃 푟푑휑 × 푟푑휃 Irradiance • Now, let’s assume that we are interested in computing the total amount of light arriving at some point on a surface • We are essentially integrating over all possible directions in the hemisphere above the surface (assuming it’s opaque and we’re not receiving translucent light from below the surface) • We are integrating the light intensity (or radiance) coming in from every direction • The total incoming radiance over all directions in the hemisphere -
Radiosity Radiosity
Radiosity Radiosity Motivation: what is missing in ray-traced images? Indirect illumination effects Color bleeding Soft shadows Radiosity is a physically-based illumination algorithm capable of simulating the above phenomena in a scene made of ideal diffuse surfaces. Books: Cohen and Wallace, Radiosity and Realistic Image Synthesis, Academic Press Professional 1993. Sillion and Puech, Radiosity and Global Illumination, Morgan- Kaufmann, 1994. Indirect illumination effects Radiosity in a Nutshell Break surfaces into many small elements Light source Formulate and solve a linear system of equations that models the equilibrium of inter-reflected Eye light in a scene. Diffuse Reflection The solution gives us the amount of light leaving each point on each surface in the scene. Once solution is computed, the shaded elements can be quickly rendered from any viewpoint. Meshing (partition into elements) Radiosity Input geometry Change geometry Form-Factors Change light or colors Solution Render Change view 1 Radiometric quantities The Radiosity Equation Radiant energy [J] Assume that surfaces in the scene have been discretized into n small elements. Radiant power (flux): radiant energy per second [W] Assume that each element emits/reflects light Irradiance (flux density): incident radiant power per uniformly across its surface. unit area [W/m2] Define the radiosity B as the total hemispherical Radiosity (flux density): outgoing radiant power per flux density (W/m2) leaving a surface. unit area [W/m2] Let’’s write down an expression describing the total flux (light power) leaving element i in the Radiance (angular flux dedensity):nsity): radiant power per scene: unit projected area per unit solid angle [W/(m2 sr)] scene: total flux = emitted flux + reflected flux The Radiosity Equation The Form Factor Total flux leaving element i: Bi Ai The form factor Fji tells us how much of the flux Total flux emitted by element i: Ei Ai leaving element j actually reaches element i. -
Adjoints and Importance in Rendering: an Overview
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL. 9, NO. 3, JULY-SEPTEMBER 2003 1 Adjoints and Importance in Rendering: An Overview Per H. Christensen Abstract—This survey gives an overview of the use of importance, an adjoint of light, in speeding up rendering. The importance of a light distribution indicates its contribution to the region of most interest—typically the directly visible parts of a scene. Importance can therefore be used to concentrate global illumination and ray tracing calculations where they matter most for image accuracy, while reducing computations in areas of the scene that do not significantly influence the image. In this paper, we attempt to clarify the various uses of adjoints and importance in rendering by unifying them into a single framework. While doing so, we also generalize some theoretical results—known from discrete representations—to a continuous domain. Index Terms—Rendering, adjoints, importance, light, ray tracing, global illumination, participating media, literature survey. æ 1INTRODUCTION HE use of importance functions started in neutron importance since it indicates how much the different parts Ttransport simulations soon after World War II. Im- of the domain contribute to the solution at the most portance was used (in different disguises) from 1983 to important part. Importance is also known as visual accelerate ray tracing [2], [16], [27], [78], [79]. Smits et al. [67] importance, view importance, potential, visual potential, value, formally introduced the use of importance for global -
RADIATION HEAT TRANSFER Radiation
MODULE I RADIATION HEAT TRANSFER Radiation Definition Radiation, energy transfer across a system boundary due to a T, by the mechanism of photon emission or electromagnetic wave emission. Because the mechanism of transmission is photon emission, unlike conduction and convection, there need be no intermediate matter to enable transmission. The significance of this is that radiation will be the only mechanism for heat transfer whenever a vacuum is present. Electromagnetic Phenomena. We are well acquainted with a wide range of electromagnetic phenomena in modern life. These phenomena are sometimes thought of as wave phenomena and are, consequently, often described in terms of electromagnetic wave length, . Examples are given in terms of the wave distribution shown below: m UV X Rays 0.4-0.7 Thermal , ht Radiation Microwave g radiation Visible Li 10-5 10-4 10-3 10-2 10-1 10-0 101 102 103 104 105 Wavelength, , m One aspect of electromagnetic radiation is that the related topics are more closely associated with optics and electronics than with those normally found in mechanical engineering courses. Nevertheless, these are widely encountered topics and the student is familiar with them through every day life experiences. From a viewpoint of previously studied topics students, particularly those with a background in mechanical or chemical engineering, will find the subject of Radiation Heat Transfer a little unusual. The physics background differs fundamentally from that found in the areas of continuum mechanics. Much of the related material is found in courses more closely identified with quantum physics or electrical engineering, i.e. Fields and Waves. -
LIGHT TRANSPORT SIMULATION in REFLECTIVE DISPLAYS By
LIGHT TRANSPORT SIMULATION IN REFLECTIVE DISPLAYS by Zhanpeng Feng, B.S.E.E., M.S.E.E. A Dissertation In ELECTRICAL ENGINEERING DOCTOR OF PHILOSOPHY Dr. Brian Nutter Chair of the Committee Dr. Sunanda Mitra Dr. Tanja Karp Dr. Richard Gale Dr. Peter Westfall Peggy Gordon Miller Dean of the Graduate School May, 2012 Copyright 2012, Zhanpeng Feng Texas Tech University, Zhanpeng Feng, May 2012 ACKNOWLEDGEMENTS The pursuit of my Ph.D. has been a rather long journey. The journey started when I came to Texas Tech ten years ago, then took a change in direction when I went to California to work for Qualcomm in 2006. Over the course, I am privileged to have met the most amazing professionals in Texas Tech and Qualcomm. Without them I would have never been able to finish this dissertation. I begin by thanking my advisor, Dr. Brian Nutter, for introducing me to the brilliant world of research, and teaching me hands on skills to actually get something done. Dr. Nutter sets an example of excellence that inspired me to work as an engineer and researcher for my career. I would also extend my thanks to Dr. Mitra for her breadth and depth of knowledge; to Dr. Karp for her scientific rigor; to Dr. Gale for his expertise in color science and sense of humor; and to Dr. Westfall, for his great mind in statistics. They have provided me invaluable advice throughout the research. My colleagues and supervisors in Qualcomm also gave tremendous support and guidance along the path. Tom Fiske helped me establish my knowledge in optics from ground up and taught me how to use all the tools for optical measurements. -
The Photon Mapping Method
7 The Photon Mapping Method “I get by with a little help from my friends.” —John Lennon, 1940–1980 HOTON mapping is a practical approach for computing global illumination within complex P environments. Much like irradiance caching methods, photon mapping caches and reuses illumination information in the scene for efficiency. Photon mapping has also been successfully applied for computing lighting within, and in the presence of, participating media. In this chapter we briefly introduce the photon mapping technique. This sets the foundation for our contributions in the next chapter, which make volumetric photon mapping practical. 7.1 Algorithm Overview Photon mapping, introduced by Jensen[1995; 1996; 1997; 1998; 2001], is a practical approach for computing global illumination. At a high level, the algorithm consists of two main steps: Algorithm 7.1:PHOTONMAPPING() 1 PHOTONTRACING(); 2 RENDERUSINGPHOTONMAP(); In the first step, a lighting simulation is performed by tracing packets of energy, or photons, from light sources and storing these photons as they scatter within the scene. This processes 119 120 Algorithm 7.2:PHOTONTRACING() 1 n 0; e Æ 2 repeat 3 (l, pdf (l)) = CHOOSELIGHT(); 4 (xp , ~!p , ©p ) = GENERATEPHOTON(l ); ©p 5 TRACEPHOTON(xp , ~!p , pdf (l) ); 6 n 1; e ÅÆ 7 until photon map full ; 1 8 Scale power of all photons by ; ne results in a set of photon maps, which can be used to efficiently query lighting information. In the second pass, the final image is rendered using Monte Carlo ray tracing. This rendering step is made more efficient by exploiting the lighting information cached in the photon map. -
Causes of Color Radiometry for Color
Causes of color • The sensation of color is caused • Light could be produced in by the brain. different amounts at different wavelengths (compare the sun and • Some ways to get this sensation a fluorescent light bulb). include: • Light could be differentially – Pressure on the eyelids reflected (e.g. some pigments). – Dreaming, hallucinations, etc. • It could be differentially refracted - • Main way to get it is the (e.g. Newton’s prism) response of the visual system to • Wavelength dependent specular the presence/absence of light at reflection - e.g. shiny copper penny various wavelengths. (actually most metals). • Flourescence - light at invisible wavelengths is absorbed and reemitted at visible wavelengths. Computer Vision - A Modern Approach Set: Color Radiometry for color • All definitions are now “per unit wavelength” • All units are now “per unit wavelength” • All terms are now “spectral” • Radiance becomes spectral radiance – watts per square meter per steradian per unit wavelength • Radiosity --- spectral radiosity Computer Vision - A Modern Approach Set: Color 1 Black body radiators • Construct a hot body with near-zero albedo (black body) – Easiest way to do this is to build a hollow metal object with a tiny hole in it, and look at the hole. • The spectral power distribution of light leaving this object is a simple function of temperature Ê 1 ˆ Ê 1 ˆ E(l) µ 5 Á ˜ Ë l ¯ Ë exp(hc klT )-1¯ • This leads to the notion of color temperature --- the temperature of a black body that would look the same Computer Vision - A Modern Approach Set: Color Measurements of relative spectral power of sunlight, made by J. -
Lighting - the Radiance Equation
CHAPTER 3 Lighting - the Radiance Equation Lighting The Fundamental Problem for Computer Graphics So far we have a scene composed of geometric objects. In computing terms this would be a data structure representing a collection of objects. Each object, for example, might be itself a collection of polygons. Each polygon is sequence of points on a plane. The ‘real world’, however, is ‘one that generates energy’. Our scene so far is truly a phantom one, since it simply is a description of a set of forms with no substance. Energy must be generated: the scene must be lit; albeit, lit with virtual light. Computer graphics is concerned with the construction of virtual models of scenes. This is a relatively straightforward problem to solve. In comparison, the problem of lighting scenes is the major and central conceptual and practical problem of com- puter graphics. The problem is one of simulating lighting in scenes, in such a way that the computation does not take forever. Also the resulting 2D projected images should look as if they are real. In fact, let’s make the problem even more interesting and challenging: we do not just want the computation to be fast, we want it in real time. Image frames, in other words, virtual photographs taken within the scene must be produced fast enough to keep up with the changing gaze (head and eye moves) of Lighting - the Radiance Equation 35 Great Events of the Twentieth Century35 Lighting - the Radiance Equation people looking and moving around the scene - so that they experience the same vis- ual sensations as if they were moving through a corresponding real scene. -
Radiometry and Photometry
Radiometry and Photometry Wei-Chih Wang Department of Power Mechanical Engineering National TsingHua University W. Wang Materials Covered • Radiometry - Radiant Flux - Radiant Intensity - Irradiance - Radiance • Photometry - luminous Flux - luminous Intensity - Illuminance - luminance Conversion from radiometric and photometric W. Wang Radiometry Radiometry is the detection and measurement of light waves in the optical portion of the electromagnetic spectrum which is further divided into ultraviolet, visible, and infrared light. Example of a typical radiometer 3 W. Wang Photometry All light measurement is considered radiometry with photometry being a special subset of radiometry weighted for a typical human eye response. Example of a typical photometer 4 W. Wang Human Eyes Figure shows a schematic illustration of the human eye (Encyclopedia Britannica, 1994). The inside of the eyeball is clad by the retina, which is the light-sensitive part of the eye. The illustration also shows the fovea, a cone-rich central region of the retina which affords the high acuteness of central vision. Figure also shows the cell structure of the retina including the light-sensitive rod cells and cone cells. Also shown are the ganglion cells and nerve fibers that transmit the visual information to the brain. Rod cells are more abundant and more light sensitive than cone cells. Rods are 5 sensitive over the entire visible spectrum. W. Wang There are three types of cone cells, namely cone cells sensitive in the red, green, and blue spectral range. The approximate spectral sensitivity functions of the rods and three types or cones are shown in the figure above 6 W. Wang Eye sensitivity function The conversion between radiometric and photometric units is provided by the luminous efficiency function or eye sensitivity function, V(λ). -
CS 184: Problems and Questions on Rendering
CS 184: Problems and Questions on Rendering Ravi Ramamoorthi Problems 1. Define the terms Radiance and Irradiance, and give the units for each. Write down the formula (inte- gral) for irradiance at a point in terms of the illumination L(ω) incident from all directions ω. Write down the local reflectance equation, i.e. express the net reflected radiance in a given direction as an integral over the incident illumination. 2. Make appropriate approximations to derive the radiosity equation from the full rendering equation. 3. Match the surface material to the formula (and goniometric diagram shown in class). Also, give an example of a real material that reasonably closely approximates the mathematical description. Not all materials need have a corresponding diagram. The materials are ideal mirror, dark glossy, ideal diffuse, retroreflective. The formulae for the BRDF fr are 4 ka(R~ · V~ ), kb(R~ · V~ ) , kc/(N~ · V~ ), kdδ(R~), ke. 4. Consider the Cornell Box (as in the radiosity lecture, assume for now that this is essentially a room with only the walls, ceiling and floor. Assume for now, there are no small boxes or other furniture in the room, and that all surfaces are Lambertian. The box also has a small rectangular white light source at the center of the ceiling.) Assume we make careful measurements of the light source intensity and dimensions of the room, as well as the material properties of the walls, floor and ceiling. We then use these as inputs to our simple OpenGL renderer. Assuming we have been completely accurate, will the computer-generated picture be identical to a photograph of the same scene from the same location? If so, why? If not, what will be the differences? Ignore gamma correction and other nonlinear transfer issues. -
Light (Technical)
Chapter 21 Light (technical) In this chapter we will describe in more detail how light and reflections are properly measured and represented. These concepts may not be necessary for doing casual com- puter graphics, but they can become important in order to do high quality rendering. Such high quality rendering is often done using stand alone software and does not use the same rendering pipeline as OpenGL. We will cover some of this material, as it is perhaps the most developed part of advanced computer graphics. This chapter will be covering material at a more advanced level than the rest of this book. For an even more detailed treatment of this material, see Jim Arvo’s PhD thesis [3] and Eric Veach’s PhD thesis [71]. There are two steps needed to understand high quality light simulation. First of all, one needs to understand the proper units needed to measure light and reflection. This understanding directly leads to equations which model how light behaves in a scene. Secondly, one needs algorithms that compute approximate solutions to these equations. These algorithms make heavy use of the ray tracing infrastructure described in Chapter 20. In this chapter we will focuson the more fundamental aspect of deriving the appropriate equations, and only touch on the subsequent algorithmic issues. For more on such issues, the interested reader should see [71, 30]. Our basic mental model of light is that of “geometric optics”. We think of light as a field of photons flying through space. In free space, each photon flies unmolested in a straight line, and each moves at the same speed. -
Photon Mapping
Photon Mapping CSE272: Advanced Image Synthesis (Spring 2010) Henrik Wann Jensen Photon mapping A two-pass method Pass 1: Build the photon map (photon tracing) Pass 2: Render the image using the photon map CSE272: Advanced Image Synthesis (Spring 2010) Henrik Wann Jensen Building the Photon Map Photon Tracing CSE272: Advanced Image Synthesis (Spring 2010) Henrik Wann Jensen Rendering using the Photon Map Rendering CSE272: Advanced Image Synthesis (Spring 2010) Henrik Wann Jensen Photon Tracing Photon emission • Projection maps • Photon scattering • Russian Roulette • The photon map data structure • Balancing the photon map • CSE272: Advanced Image Synthesis (Spring 2010) Henrik Wann Jensen 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 CSE272: Advanced Image Synthesis (Spring 2010) Henrik Wann Jensen Photon emission Given Φ Watt lightbulb. Emit N photons. Each photon has the power Φ Watt. N Photon power depends on the number of emitted • photons. Not on the number of photons in the photon map. CSE272: Advanced Image Synthesis (Spring 2010) Henrik Wann Jensen 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 ); } CSE272: Advanced Image Synthesis (Spring 2010) Henrik Wann Jensen Example: Diffuse square light - Generate random position p on square - Generate diffuse direction