An Invitation to 3-D Vision

From Images to Geometric Models

  • Yi Ma
  • Stefano Soatto
  • Jana Košecká
  • S. Shankar Sastry
Part of the Interdisciplinary Applied Mathematics book series (IAM, volume 26)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Introduction

    1. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 1-12
  3. Introductory Material

    1. Front Matter
      Pages 13-13
    2. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 15-43
    3. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 44-74
    4. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 75-106
  4. Geometry of Two Views

    1. Front Matter
      Pages 107-107
    2. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 109-170
    3. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 171-227
    4. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 228-260
  5. Geometry of Multiple Views

    1. Front Matter
      Pages 261-261
    2. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 263-309
    3. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 310-337
    4. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 338-372
  6. Applications

    1. Front Matter
      Pages 373-373
    2. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 375-411
    3. Yi Ma, Stefano Soatto, Jana Košecká, S. Shankar Sastry
      Pages 412-438
  7. Back Matter
    Pages 439-527

About this book

Introduction

Endowing machines with a sense of vision has been a dream of scientists and engineers alike for over half a century. Only in the past decade, however, has the geometry of vision been understood to the point where this dream becomes attainable, thanks also to the remarkable progress in imaging and computing hardware.

This book addresses a central problem in computer vision -- how to recover 3-D structure and motion from a collection of 2-D images -- using techniques drawn mainly from linear algebra and matrix theory. The stress is on developing a unified framework for studying the geometry of multiple images of a 3-D scene and reconstructing geometric models from those images. The book also covers relevant aspects of image formation, basic image processing, and feature extraction. The authors bridge the gap between theory and practice by providing step-by-step instructions for the implementation of working vision algorithms and systems.

Written primarily as a textbook, the aim of this book is to give senior undergraduate and beginning graduate students in computer vision, robotics, and computer graphics a solid theoretical and algorithmic foundation for future research in this burgeoning field. It is entirely self-contained with necessary background material covered in the beginning chapters and appendices, and plenty of exercises, examples, and illustrations given throughout the text.

Keywords

3D Tracking algorithms computer graphics computer vision filtering linear algebra linear optimization nonlinear optimization optimization robot robotics

Authors and affiliations

  • Yi Ma
    • 1
  • Stefano Soatto
    • 2
  • Jana Košecká
    • 3
  • S. Shankar Sastry
    • 4
  1. 1.Department of Electrical and Computer EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  2. 2.Department of Computer ScienceUniversity of California, Los AngelesLos AngelesUSA
  3. 3.Department of Computer ScienceGeorge Mason UniversityFairfaxUSA
  4. 4.Department of Electrical Engineering and Computer ScienceUniversity of California, BerkeleyBerkeleyUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-21779-6
  • Copyright Information Springer-Verlag New York 2004
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4419-1846-8
  • Online ISBN 978-0-387-21779-6
  • Series Print ISSN 0939-6047
  • About this book