Machine learning a constraint-based approach

Advanced RenderMan: Creating CGI for Motion Pictures is precisely what you and other RenderMan users are dying for. Written by the world's foremost RenderMan experts, it offers thoroughly updated coverage of the standard while moving beyond the scope of the original RenderMan Companion to provi...

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Bibliographic Details
Other Authors: Gori, Marco, author (author)
Format: eBook
Language:Inglés
Published: Amsterdam : Morgan Kaufmann 2017.
Subjects:
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009752718206719
Description
Summary:Advanced RenderMan: Creating CGI for Motion Pictures is precisely what you and other RenderMan users are dying for. Written by the world's foremost RenderMan experts, it offers thoroughly updated coverage of the standard while moving beyond the scope of the original RenderMan Companion to provide in-depth information on dozens of advanced topics. Both a reference and a tutorial, this book will quickly prove indispensable, whether you're a technical director, graphics programmer, modeler, animator, or hobbyist.Explore the Power of RenderManUse the entire range of geometric primitives supported by RenderMan.Understand how and when to use procedural primitives and level of detail.Master every nuance of the Shading Language.Write detailed procedural shaders using texture, displacement, pattern generation, and custom reflection models.Write shaders for special effects relating to volumes, custom lighting, and non-photorealistic media.Use antialiasing to ensure that your shaders are free of artifacts.Minimize the expense of rendering scenes by optimizing input.Other Features from Advanced RenderManOffers expert advice and instruction applicable to any RenderMan-compliant renderer.Filled with technical illustrations and many full-color representations of effects supported by the RenderMan standard.Includes a chapter reviewing key math and computer graphics concepts.
Item Description:The Big Picture Learning Principles Linear-Threshold Machines Kernel Machines Deep Architectures Learning and Reasoning with Constraints Epilogue Answers to selected exercises Appendices: Constrained optimization in Finite Dimensions Regularization operators Calculus of variations Index to Notations.
Physical Description:1 online resource (580 p.)