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Hierarchical Perceptual Grouping for Object Recognition

Theoretical Views and Gestalt-Law Applications

  • Eckart Michaelsen
  • Jochen Meidow

Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Eckart Michaelsen, Jochen Meidow
    Pages 1-22
  3. Eckart Michaelsen, Jochen Meidow
    Pages 23-51
  4. Eckart Michaelsen, Jochen Meidow
    Pages 53-70
  5. Eckart Michaelsen, Jochen Meidow
    Pages 71-84
  6. Eckart Michaelsen, Jochen Meidow
    Pages 85-100
  7. Eckart Michaelsen, Jochen Meidow
    Pages 101-106
  8. Eckart Michaelsen, Jochen Meidow
    Pages 107-109
  9. Eckart Michaelsen, Jochen Meidow
    Pages 111-125
  10. Eckart Michaelsen, Jochen Meidow
    Pages 127-133
  11. Eckart Michaelsen, Jochen Meidow
    Pages 135-144
  12. Eckart Michaelsen, Jochen Meidow
    Pages 145-161
  13. Eckart Michaelsen, Jochen Meidow
    Pages 163-173
  14. Eckart Michaelsen, Jochen Meidow
    Pages 175-188
  15. Back Matter
    Pages 189-195

About this book

Introduction

This unique text/reference presents a unified approach to the formulation of Gestalt laws for perceptual grouping, and the construction of nested hierarchies by aggregation utilizing these laws. The book also describes the extraction of such constructions from noisy images showing man-made objects and clutter. Each Gestalt operation is introduced in a separate, self-contained chapter, together with application examples and a brief literature review. These are then brought together in an algebraic closure chapter, followed by chapters that connect the method to the data – i.e., the extraction of primitives from images, cooperation with machine-readable knowledge, and cooperation with machine learning.

Topics and features:

  • Offers the first unified approach to nested hierarchical perceptual grouping
  • Presents a review of all relevant Gestalt laws in a single source
  • Covers reflection symmetry, frieze symmetry, rotational symmetry, parallelism and rectangular settings, contour prolongation, and lattices
  • Describes the problem from all theoretical viewpoints, including syntactic, probabilistic, and algebraic perspectives
  • Discusses issues important to practical application, such as primitive extraction and any-time search
  • Provides an appendix detailing a  general adjustment model with constraints

This work offers new insights and proposes novel methods to advance the field of machine vision, which will be of great benefit to students, researchers, and engineers active in this area.

Dr.-Ing. Eckart Michaelsen is a researcher at the Object Recognition Department of Fraunhofer IOSB, Ettlingen, Germany. Dr.-Ing. Jochen Meidow is a researcher at the Scene Analysis Department of the same institution.

Keywords

Object recognition Perceptual grouping Nested hiearchical symmetries Gestalt laws Machine vision

Authors and affiliations

  • Eckart Michaelsen
    • 1
  • Jochen Meidow
    • 2
  1. 1.Fraunhofer IOSBEttlingenGermany
  2. 2.Fraunhofer IOSBEttlingenGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-04040-6
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-04039-0
  • Online ISBN 978-3-030-04040-6
  • Series Print ISSN 2191-6586
  • Series Online ISSN 2191-6594
  • Buy this book on publisher's site
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