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Hierarchical Perceptual Grouping for Object Recognition : Theoretical Views and Gestalt-Law Applications / by Eckart Michaelsen, Jochen Meidow.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Author/Creator:
Michaelsen, Eckart, author.
Meidow, Jochen, author.
Contributor:
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
Advances in computer vision and pattern recognition 2191-6586
Advances in Computer Vision and Pattern Recognition, 2191-6586
Language:
English
Subjects (All):
Pattern perception.
Remote sensing.
Architecture.
Group theory.
Pattern Recognition.
Remote Sensing/Photogrammetry.
Architecture, general.
Group Theory and Generalizations.
Local Subjects:
Pattern Recognition.
Remote Sensing/Photogrammetry.
Architecture, general.
Group Theory and Generalizations.
Physical Description:
1 online resource (XI, 195 pages) : 100 illustrations, 9 illustrations in color.
Edition:
First edition 2019.
Contained In:
Springer eBooks
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2019.
System Details:
text file PDF
Summary:
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 - id est, 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.
Contents:
Introduction
Reflection Symmetry
Good Continuation in Rows or Frieze Symmetry
Rotational Symmetry
Closure - Hierarchies of Gestalten
Search
Illusions
Prolongation in Good Continuation
Parallelism and Rectangularity
Lattice Gestalten
Primitive Extraction
Knowledge and Gestalt Interaction
Learning
Appendix A: General Adjustment Model with Constraints.
Other Format:
Printed edition:
ISBN:
978-3-030-04040-6
9783030040406
9783030040390
9783030040413
Access Restriction:
Restricted for use by site license.

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