Physically Based Rendering: From Theory to Implementation

· Elsevier
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Rendering is a crucial component of computer graphics— the conversion of a description of a 3D scene into an image for display. Algorithms for animation, geometric modeling, and texturing all must feed their results through some sort of rendering process for the results to be visible in an image. Focusing on realistic images, physically based rendering incorporates ideas from a range of disciplines, including physics, biology, psychology, cognitive science, and mathematics. This book presents the algorithms of modern photorealistic rendering and follows step by step the creation of a complete rendering system. As each new rendering concept is introduced it is also shown implemented in code—there is no better way to understand the subtle and complex process of rendering. The code itself is highly readable, written in the literate programming style that mixes text describing the system with the code that implements it. The result is a stunning achievement in graphics education for students, professionals, and researchers.

*CD-ROM with the source code for a complete rendering system for Windows, OS X, & Linux—with many examples of images created by the system throughout the 4 color text
*The code and text are tightly woven together through the technique of literate programming with a unique indexing feature that lists all locations of functions, variables, and methods on the page they are first described
*The most complete guide to understanding, designing, and building a rendering system

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5,0
2 reseñas

Acerca del autor

Matt Pharr is a Software Engineer at Google. He previously co-founded Neoptica, which was acquired by Intel, and co-founded Exluna, which was acquired by NVIDIA. He has a B.S. degree from Yale and a Ph.D. from the Stanford Graphics Lab, where he worked under the supervision of Pat Hanrahan.

Greg Humphreys is Director of Engineering at FanDuel, having previously worked on the Chrome graphics team at Google and the OptiX GPU raytracing engine at NVIDIA. Before that, he was a professor of Computer Science at the University of Virginia, where he conducted research in both high performance and physically based computer graphics, as well as computer architecture and visualization. Greg has a B.S.E. degree from Princeton, and a Ph.D. in Computer Science from Stanford under the supervision of Pat Hanrahan. When he's not tracing rays, Greg can usually be found playing tournament bridge.

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