Image-based Rendering

by Shum, Heung-Yeung; Chan, Shing-chow; Kang, Sing Bing

• ISBN13: 9780387211138
• ISBN10: 0387211136
• Format: Hardcover
• Copyright: 2006-11-30
• Publisher: Springer-Verlag New York Inc

Summary

Image-based rendering (IBR) refers to a collection of techniques and representations that allow 3D scenes and objects to be visualized in a realistic way without full 3D model reconstruction. IBR uses images as the primary substrate. The potential for photorealistic visualization has tremendous appeal, and it is thus not surprising that IBR has been receiving increasing attention over the years. Applications such as video games, virtual travel, and E-commerce stand to benefit from this technology. Image-Based Rendering examines the theory, practice, and applications associated with image-based rendering and modeling. The authors bring together their backgrounds and research experiences in computer graphics, computer vision and signal processing to address the multi-disciplinary nature of IBR research. The topics to be covered vary from IBR basic concepts and representations on the theory side, to signal processing and data compression on the practical side. These theoretical and practical issues are further disseminated in several IBR systems built to-date. However, this book will not focus on the geometrical modeling aspect of IBR, since 3D modeling has been extensively treated elsewhere in the vision literature. One of the only titles devoted exclusively to the area of IBR, this book is intended for researchers, professionals, and general readers interested in the topics of computer graphics, computer vision, image processing, and video processing. Advanced-level students in EECS studying related disciplines will be able to seriously expand their knowledge about image-based rendering.

Table of Contents

Foreword

Preface

Acknowledgements

Introduction

Basic Concepts: Direct Image Representations

Representations with Explicit Geometry

Rendering Dynamic Scenes

Representation and Rendering Issues

Sampling: Plenoptic Sampling

A Geometric Analysis of Light Field Rendering

Sampling in Dual Space

Bibliography

Compression: Data Compression Techniques

Image and Video Compression

Compression of Static Image-based Representations

Compression of Dynamic Image-based Representations

Systems and Applications

Large Environment Rendering Using Plenoptic Primitives

Pop-Up Light Field

Feature-based Light Field Morphing

Concluding Remarks

Bibliography

Table of Contents provided by Publisher. All Rights Reserved.