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Measurement of Image Velocity

  • David J. Fleet

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Background

    1. Front Matter
      Pages 1-1
    2. David J. Fleet
      Pages 3-10
    3. David J. Fleet
      Pages 11-17
    4. David J. Fleet
      Pages 19-28
    5. David J. Fleet
      Pages 29-36
    6. David J. Fleet
      Pages 37-49
  3. Phase-Based Velocity Measurement

    1. Front Matter
      Pages 51-54
    2. David J. Fleet
      Pages 55-66
    3. David J. Fleet
      Pages 67-84
    4. David J. Fleet
      Pages 85-99
  4. On Phase Properties of Band-Pass Signals

    1. Front Matter
      Pages 101-104
    2. David J. Fleet
      Pages 105-118
    3. David J. Fleet
      Pages 119-132
    4. David J. Fleet
      Pages 133-147
  5. Conclusions

    1. Front Matter
      Pages 149-149
    2. David J. Fleet
      Pages 151-156
  6. Back Matter
    Pages 157-203

About this book

Introduction

Measurement of Image Velocity presents a computational framework for computing motion information from sequences of images. Its specific goal is the measurement of image velocity (or optical flow), the projection of 3-D object motion onto the 2-D image plane.
The formulation of the problem emphasizes the geometric and photometric properties of image formation, and the occurrence of multiple image velocities caused, for example, by specular reflections, shadows, or transparency. The method proposed for measuring image velocity is based on the phase behavior in the output of velocity-tuned filters. Extensive experimental work is used to show that phase can be a reliable source of pure image translation, small geometric deformation, smooth contrast variations, and multiple local velocities. Extensive theorectical analysis is used to explain the robustness of phase with respect to deviations from image translation, and to detect situations in which phase becomes unstable. The results indicate that optical flow may be extracted reliably for computing egomotion and structure from motion.
The monograph also contains a review of other techniques and frequency analysis applied to image sequences, and it discusses the closely related topics of zero-crossing tracking, gradient-based methods, and the measurement of binocular disparity. The work is relevant to those studying machine vision and visual perception.

Keywords

Interpolation Optical flow Tracking behavior machine vision measurement perception reflection stability uncertainty

Authors and affiliations

  • David J. Fleet
    • 1
  1. 1.Queen’s UniversityCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-3648-2
  • Copyright Information Kluwer Academic Publishers 1992
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-6623-2
  • Online ISBN 978-1-4615-3648-2
  • Series Print ISSN 0893-3405
  • Buy this book on publisher's site
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