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3D Dynamic Scene Analysis

A Stereo Based Approach

  • Zhengyou Zhang
  • Olivier Faugeras

Part of the Springer Series in Information Sciences book series (SSINF, volume 27)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Zhengyou Zhang, Olivier Faugeras
    Pages 1-8
  3. Zhengyou Zhang, Olivier Faugeras
    Pages 9-27
  4. Zhengyou Zhang, Olivier Faugeras
    Pages 29-38
  5. Zhengyou Zhang, Olivier Faugeras
    Pages 39-54
  6. Zhengyou Zhang, Olivier Faugeras
    Pages 55-80
  7. Zhengyou Zhang, Olivier Faugeras
    Pages 81-98
  8. Zhengyou Zhang, Olivier Faugeras
    Pages 99-126
  9. Zhengyou Zhang, Olivier Faugeras
    Pages 127-144
  10. Zhengyou Zhang, Olivier Faugeras
    Pages 145-158
  11. Zhengyou Zhang, Olivier Faugeras
    Pages 159-168
  12. Zhengyou Zhang, Olivier Faugeras
    Pages 169-186
  13. Zhengyou Zhang, Olivier Faugeras
    Pages 187-204
  14. Zhengyou Zhang, Olivier Faugeras
    Pages 205-216
  15. Zhengyou Zhang, Olivier Faugeras
    Pages 217-237
  16. Zhengyou Zhang, Olivier Faugeras
    Pages 239-271
  17. Zhengyou Zhang, Olivier Faugeras
    Pages 273-276
  18. Back Matter
    Pages 277-300

About this book

Introduction

he problem of analyzing sequences of images to extract three-dimensional T motion and structure has been at the heart of the research in computer vi­ sion for many years. It is very important since its success or failure will determine whether or not vision can be used as a sensory process in reactive systems. The considerable research interest in this field has been motivated at least by the following two points: 1. The redundancy of information contained in time-varying images can over­ come several difficulties encountered in interpreting a single image. 2. There are a lot of important applications including automatic vehicle driv­ ing, traffic control, aerial surveillance, medical inspection and global model construction. However, there are many new problems which should be solved: how to effi­ ciently process the abundant information contained in time-varying images, how to model the change between images, how to model the uncertainty inherently associated with the imaging system and how to solve inverse problems which are generally ill-posed. There are of course many possibilities for attacking these problems and many more remain to be explored. We discuss a few of them in this book based on work carried out during the last five years in the Computer Vision and Robotics Group at INRIA (Institut National de Recherche en Informatique et en Automatique).

Keywords

Vision artificial intelligence computer vision image processing intelligence modeling motion estimation navigation noise robot robotics uncertainty

Authors and affiliations

  • Zhengyou Zhang
    • 1
  • Olivier Faugeras
    • 1
  1. 1.INRIA Sophia AntipolisSophia Antipolis CedexFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-58148-9
  • Copyright Information Springer-Verlag Ber Heidelberg 1992
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-63485-7
  • Online ISBN 978-3-642-58148-9
  • Series Print ISSN 0720-678X
  • Buy this book on publisher's site