Physically Based Rendering: From Theory to Implementation, Third Edition, describes both the mathematical theory behind a modern photorealistic rendering system and its practical implementation. Through a method known as 'literate programming', the authors combine human-readable documentation and source code into a single reference that is specifically designed to aid comprehension. The result is a stunning achievement in graphics education. Through the ideas and software in this book, users will learn to design and employ a fully-featured rendering system for creating stunning imagery. This completely updated and revised edition includes new coverage on ray-tracing hair and curves primitives, numerical precision issues with ray tracing, LBVHs, realistic camera models, the measurement equation, and much more. It is a must-have, full color resource on physically-based rendering. Presents up-to-date revisions of the seminal reference on rendering, including new sections on bidirectional path tracing, numerical robustness issues in ray tracing, realistic camera models, and subsurface scattering Provides the source code for a complete rendering system allowing readers to get up and running fast Includes a unique indexing feature, literate programming, that lists the locations of each function, variable, and method on the page where they are first described Serves as an essential resource on physically-based rendering
This thesis presents methods for photorealistic rendering of virtual objects so that they can be seamlessly composited into images of the real world. To generate predictable and consistent results, we study physically based methods, which simulate how light propagates in a mathematical model of the augmented scene. This computationally challenging problem demands both efficient and accurate simulation of the light transport in the scene, as well as detailed modeling of the geometries, illumination conditions, and material properties. In this thesis, we discuss and formulate the challenges inherent in these steps and present several methods to make the process more efficient. In particular, the material contained in this thesis addresses four closely related areas: HDR imaging, IBL, reflectance modeling, and efficient rendering. The thesis presents a new, statistically motivated algorithm for HDR reconstruction from raw camera data combining demosaicing, denoising, and HDR fusion in a single processing operation. The thesis also presents practical and robust methods for rendering with spatially and temporally varying illumination conditions captured using omnidirectional HDR video. Furthermore, two new parametric BRDF models are proposed for surfaces exhibiting wide angle gloss. Finally, the thesis also presents a physically based light transport algorithm based on Markov Chain Monte Carlo methods that allows approximations to be used in place of exact quantities, while still converging to the exact result. As illustrated in the thesis, the proposed algorithm enables efficient rendering of scenes with glossy transfer and heterogenous participating media.
Physically Based Rendering, Second Edition, describes both the mathematical theory behind a modern photorealistic rendering system as well as its practical implementation. A method known as literate programming combines human-readable documentation and source code into a single reference that is specifically designed to aid comprehension. The result is a stunning achievement in graphics education. Through the ideas and software in this book, you will learn to design and employ a full-featured rendering system for creating stunning imagery. This new edition greatly refines its best-selling predecessor by streamlining all obsolete code as well as adding sections on parallel rendering and system design; animating transformations; multispectral rendering; realistic lens systems; blue noise and adaptive sampling patterns and reconstruction; measured BRDFs; and instant global illumination, as well as subsurface and multiple-scattering integrators. These updates reflect the current state-of-the-art technology, and along with the lucid pairing of text and code, ensure the book's leading position as a reference text for those working with images, whether it is for film, video, photography, digital design, visualization, or gaming. The book that won its authors a 2014 Academy Award for Scientific and Technical Achievement from the Academy of Motion Picture Arts and Sciences New sections on subsurface scattering, Metropolis light transport, precomputed light transport, multispectral rendering, and much more Includes a companion site complete with source code for the rendering system described in the book, with support for Windows, OS X, and Linux: visit www.pbrt.org Code and text are tightly woven together through a unique indexing feature that lists each function, variable, and method on the page that they are first described.
Learn Physically Based Rendering with Allegorithmic’s Substance Painter
Author: Abhishek Kumar
Delve into the concepts of physically based rendering (PBR) using Allegorithmic’s Substance Painter. This book covers the integration of PBR textures with various 3D modeling and rendering packages as well as with the Unreal Engine 4 game engine. Beginning PBR Texturing covers all aspects of the software and guides you in implementing its incredible possibilities, including using materials, masks, and baking. Integration with both internal and popular external rendering engines is covered. This book teaches you the skills you need to use the texturing tool that is recognized by studios worldwide. You will know tips and tricks to implement the pipeline and speed up your workflow. What You Will Learn Know the fundamentals of PBR-based texturing from the ground up Create production-ready textured models from scratch Integrate PBR textures with standard 3D modeling and rendering applications Create portfolio-ready renders using offline renderers Who This Book Is For Beginners in the fields of 3D animation, computer graphics, and game technology
In this dissertation, we focus on physically-based rendering that synthesizes realistic images from 3D models and scenes. State of the art rendering still struggles with two fundamental challenges -- realism and speed. The rendered results look artificial and overly perfect, and the rendering process is slow for both offline and interactive applications. Moreover, better realism and faster speed are inherently contradictory, because the computational complexity increases substantially when trying to render higher fidelity detailed results. We put emphasis on both ends of the realism-speed spectrum in rendering by introducing the concept of detailed rendering and appearance modeling to accurately represent and reproduce the rich visual world from micron level to overall appearance, and combining sparse ray sampling with fast high dimensional filtering to achieve real-time performance. To make rendering more realistic, our first claim is that, we need details. However, rendering a complex surface with lots of details is far from easy. Traditionally, the surface microstructure is approximated using a smooth normal distribution, but this ignores details such as glinty effects, easily observable in the real world. While modeling the actual surface microstructure is possible, the resulting rendering problem is prohibitively expensive using Monte Carlo point sampling: the energy is concentrated in tiny highlights that take up a minuscule fraction of the pixel. We instead compute the accurate solution that Monte Carlo would eventually converge to, using a completely different deterministic approach (Chapter 3). Our method considers the highly complicated distribution of normals on a surface patch seen through a single pixel. We show different methods to evaluate this efficiently with closed-form solutions, assuming a surface patch is made up of either 2D planar triangles or 4D Gaussian elements, respectively. We also show how to extend our method to accurately handle wave optics. Our results show complicated, temporally varying glints from materials such as bumpy plastics, brushed and scratched metals, metallic paint and ocean waves. In the above, although rendering details imposes many challenges, we assumed we know how the surface reflects light. However, there are a lot of natural materials in the real world where we are not sure exactly how they interact with the light. To render these materials realistically, we need accurate appearance/reflectance models derived from microstructures to define their optical behavior. We demonstrate this by introducing a reflectance model for animal fur in Chapter 4. Rendering photo-realistic animal fur is a long-standing problem in computer graphics. Considerable effort has been made on modeling the geometric complexity of human hair, but the appearance/reflectance of fur fibers is not well understood. Based on anatomical literature and measurements, we develop a double cylinder model for the reflectance of a single fur fiber, where an outer cylinder represents the biological observation of a cortex covered by multiple cuticle layers, and an inner cylinder represents the scattering interior structure known as the medulla, often absent from human hair fibers. We validate our physical model with measurements on real fur fibers, and introduce the first database in computer graphics of reflectance profiles for nine fur samples. For efficient rendering, we develop a method to precompute 2D medulla scattering profiles and analytically approximate our reflectance model with factored lobes. We then develop a number of optimizations that improve efficiency and generality without compromising accuracy. And we present the first global illumination model, based on dipole diffusion for subsurface scattering, to approximate light bouncing between individual fur fibers by modeling complex light and fur interactions as subsurface scattering, and using a simple neural network to convert from fur fibers' properties to scattering parameters. However, even without these details to improve rendered realism, current rendering still suffers from low performance with state of the art Monte Carlo ray tracing. Physically correct, noise-free images can require hundreds or thousands of ray samples per pixel, and take a long time to compute. Recent approaches have exploited sparse sampling and filtering; the filtering is either fast (axis-aligned), but requires more input samples, or needs fewer input samples but is very slow (sheared). We present a new approach for fast sheared filtering on the GPU in Chapter 5. Our algorithm factors the 4D sheared filter into four 1D filters. We derive complexity bounds for our method, showing that the per-pixel complexity is reduced from O(n^2 l^2)$ to O(nl), where n is the linear filter width (filter size is O(n^2)) and l is the (usually very small) number of samples for each dimension of the light or lens per pixel (spp is l^2). We thus reduce sheared filtering overhead dramatically. We demonstrate rendering of depth of field, soft shadows and diffuse global illumination at interactive speeds.
This thesis explores a set of screen space physically-based subsurface scattering algorithms in order to improve the rendering of scanned human faces. Moreover, it presents extensions and introduces some PBR strategies to produce high quality renders. Finally, the implemented methods are evaluated.
Benefit from the latest rendering tech developments, currently covered only in papers and talks from Siggraph, in a way any developer or technical artist using Unity can take advantage of. This book starts by introducing how shader programming works in general, the common principles of different platforms (OpenGL, Vulkan, and DirectX), and the shading languages Unity uses: Cg, GLSL, and ShaderLab. Physically Based Shader Development for Unity 2017 discusses artistic choices, presenting various techniques (such as translucency and subsurface scattering) and BRDFs (Oren-Nayar, Cook-Torrance, and Ashikhmin-Shirley), and what they can be used for. Finally you’ll cover the importance of optimizing your code by developing approximations, which achieve similar end results, but are computationally cheaper. By the end of your journey you’ll be able to develop the look of your game or Unity-rendered animated short so that it looks both unique and impressively realistic, thanks to your own custom lighting system. What You Will Learn Master shader programming Gain all you need to know about physically based shading Take almost full control of the shader subsystem Discover what you can achieve with that control Implement a custom physically based lighting system and examine the logic behind every choice Who This Book Is For Most game developers (both indie and AA) that use Unity and technical artists who are responsible for the final look of a game.
Focusing exclusively on Image-Based Rendering (IBR) this book examines the theory, practice, and applications associated with image-based rendering and modeling. Topics covered vary from IBR basic concepts and representations on the theory side to signal processing and data compression on the practical side. One of the only titles devoted exclusively to IBR this book is intended for researchers, professionals, and general readers interested in the topics of computer graphics, computer vision, image process, and video processing. With this book advanced-level students in EECS studying related disciplines will be able to seriously expand their knowledge about image-based rendering.
This carefully chosen collection surveys the state of the art and presents new techniques covering the following main areas: • Radiance transfer • Camera, sound and painting • Scattering, translucency and soft shadows • Illumination and perception • Trees, shells and flows • Images and videos The 18th Eurographics Symposium on Rendering was held in Grenoble, France from May 25-27, 2007. This is an event in a series of highly successful Eurographics Symposia on Rendering and the Eurographics Workshops on Rendering, held over the past 17 years.
We then use the color histogram analysis techniques in a digital photographic application to extract the spectral information about the illumination in the scene and spectral information about the diffuse component of the reflectance of a dichromatic surface. This spectral information is then used to predict the appearance of objects in the image under different illumination spectra. Our method is demonstrated to show improved performance over some traditional illumination compensation methods, and has great potential in digital photography.