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Image-Based Rendering

  • Heung-Yeung Shum
  • Shing-Chow Chan
  • Sing Bing Kang

Table of contents

  1. Front Matter
    Pages i-xx
  2. Introduction

    1. Pages 1-5
  3. Representations and Rendering Techniques

    1. Front Matter
      Pages 7-8
    2. Pages 71-90
  4. Sampling

  5. Compression

  6. Systems and Applications

  7. Back Matter
    Pages 385-417

About this book

Introduction

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.

Keywords

3D 3D modeling Computer vision Modeling Morphing Performance Sampling Video & image compression Visualization computer graphics data compression image processing rendering

Authors and affiliations

  • Heung-Yeung Shum
  • Shing-Chow Chan
    • 1
  • Sing Bing Kang
    • 2
  1. 1.University of Hong KongHong Kong
  2. 2.Microsoft ResearchUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-32668-9
  • Copyright Information Springer Science+Business Media, Inc. 2007
  • Publisher Name Springer, Boston, MA
  • eBook Packages Computer Science
  • Print ISBN 978-0-387-21113-8
  • Online ISBN 978-0-387-32668-9
  • Buy this book on publisher's site