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|a 9780387326689
|9 978-0-387-32668-9
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|a 10.1007/978-0-387-32668-9
|2 doi
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|a TA1501-1820
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|a Shum, Heung-Yeung.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Image-Based Rendering
|h [electronic resource] /
|c by Heung-Yeung Shum, Shing-Chow Chan, Sing Bing Kang.
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|a 1st ed. 2007.
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|a New York, NY :
|b Springer US :
|b Imprint: Springer,
|c 2007.
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|a XX, 408 p. 95 illus.
|b online resource.
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|a text
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|a online resource
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|b PDF
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|a Representations and Rendering Techniques -- Static Scene Representations -- Rendering Dynamic Scenes -- Rendering Techniques -- Sampling -- Plenoptic Sampling -- Geometric Analysis of Light Field Rendering -- Optical Analysis of Light Field Rendering -- Optimizing Rendering Performance using Sampling Analysis -- Compression -- to Compression -- Image Compression Techniques -- Video Compression Techniques -- Compression of Static Image-based Representations -- Compression of Dynamic Image-based Representations -- Systems and Applications -- Rendering by Manifold Hopping -- Large Environment Rendering using Plenoptic Primitives -- Pop-Up Light Field: An Interactive Image-Based Modeling and Rendering System -- Feature-Based Light Field Morphing.
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|a Image-based rendering (IBR) refers to a collection of techniques and representations that allows 3D scenes and objects to be visualized in a realistic way without full 3D model reconstruction. The potential for photorealistic visualization has tremendous appeal, especially for applications such as video games, virtual travel, and E-commerce, which stand to greatly benefit from this technology. Image-Based Rendering examines the theory, practice, and applications associated with image-based rendering and modeling. As leading researchers in the field, the authors combine their unique experiences in computer graphics, computer vision, and signal processing to address the multidisciplinary nature of IBR research. The text is divided into three parts: Representations and Rendering Techniques, Sampling, and Compression. The topics covered vary from IBR basic concepts and representations on the theory side to signal processing and data compression on the practical side and examines several IBR systems built to-date. This title is exceptional in its extensive focus on image-based rendering and is intended for researchers, professionals, and general readers interested in the topics of computer graphics, computer vision, image process, and video processing. Advanced-level students in EECS studying related disciplines will be able to expand their knowledge of IBR. Providing the reader with both historical background and the technical concepts and advances in the field, Image-Based Rendering is an invaluable reference tool and guide to new discoveries and applications.
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|a Image processing-Digital techniques.
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|a Computer vision.
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|a Computer graphics.
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|a Signal processing.
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|a Multimedia systems.
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|a Computer Imaging, Vision, Pattern Recognition and Graphics.
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|a Computer Graphics.
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|a Computer Vision.
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|a Signal, Speech and Image Processing .
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|a Multimedia Information Systems.
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|a Chan, Shing-Chow.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Kang, Sing Bing.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9780387522869
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|i Printed edition:
|z 9781441935458
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|i Printed edition:
|z 9780387211138
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|u https://doi.uam.elogim.com/10.1007/978-0-387-32668-9
|z Texto Completo
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|a ZDB-2-SCS
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|a ZDB-2-SXCS
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|a Computer Science (SpringerNature-11645)
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|a Computer Science (R0) (SpringerNature-43710)
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