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Shape Perception in Human and Computer Vision : an Interdisciplinary Perspective.

Author: Sven J Dickinson; Zygmunt Pizlo
Publisher: Dordrecht : Springer, 2013.
Series: Advances in computer vision and pattern recognition.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
This comprehensive and authoritative text/reference presents a unique, multidisciplinary perspective on Shape Perception in Human and Computer Vision. Rather than focusing purely on the state of the art, the book provides viewpoints from world-class researchers reflecting broadly on the issues that have shaped the field. Drawing upon many years of experience, each contributor discusses the trends followed and the  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Dickinson, Sven J.
Shape Perception in Human and Computer Vision : An Interdisciplinary Perspective.
Dordrecht : Springer, ©2013
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Sven J Dickinson; Zygmunt Pizlo
ISBN: 9781447151951 144715195X
OCLC Number: 854976130
Notes: 6.4 Part III. From Mid- to Higher-Level Vision: Linking Shape Perception to Categorization.
Description: 1 online resource (504 pages).
Contents: Shape Perception in Human and Computer Vision; Preface; Contents; Contributors; Chapter 1: The Role of Mid-Level Shape Priors in Perceptual Grouping and Image Abstraction; 1.1 Introduction; 1.2 Symmetric Part Detection and Grouping; 1.3 Contour Closure; 1.4 Abstract Part Recovery; 1.5 Conclusions; References; Chapter 2: Symmetry Is the sine qua non of Shape; 2.1 Introduction; 2.2 Prior Definitions of Shape; 2.3 Explanation of the New Definition and How We Worked It out; 2.4 Symmetry Groups for 3D Shapes, Their Invariants and Invariants of the Perspective Projection. 2.5 Inferring 3D Shape from a 3D Object2.6 Computational and Psychophysical Implications of the New Definition; 2.6.1 Veridical Perception of 3D Shapes; 2.6.2 Shapes of Non-rigid Objects; 2.6.3 Symmetry as an Objective, but Informative, Prior; 2.6.4 Shape Constancy: View-Invariant vs. View-Dependent Shape Perception; 2.7 Conclusion; References; Chapter 3: Flux Graphs for 2D Shape Analysis; 3.1 Introduction; 3.2 Full Boundary Reconstruction; 3.2.1 Boundary Representation Through Regular Points with First-Order Approximation of the Tangent Vector; 3.2.2 Full Boundary Reconstruction. 3.3 Salient Parts of the Medial Axis3.3.1 Simplifying the Skeleton; 3.4 Flux Graphs; 3.4.1 Nodes and Edges; 3.4.2 Qualitative Stability with Viewpoint Changes; 3.5 Flux Graphs for Matching; 3.5.1 Topological and Geometrical Similarity; 3.5.2 The DAG Matcher; 3.5.3 The Dataset and Experimental Results; 3.5.4 Flux Graphs versus Shock Graphs; 3.5.5 Matching 2-D Views of 3-D Models; 3.6 Conclusion; References; Chapter 4: An Integrated Bayesian Approach to Shape Representation and Perceptual Organization; 4.1 Shape and Perceptual Organization; 4.2 Bayesian Estimation of the Shape Skeleton. 4.2.1 Sketch of the Theory4.3 Applications and Extensions; 4.3.1 Decomposing Shapes into Parts; 4.3.2 Tuning the Shape Model to the Environment; 4.3.3 Shape Similarity; 4.3.4 Figure and Ground; 4.3.5 3D Shape; 4.4 Discussion and Conclusion; References; Chapter 5: Perceptual Organization of Shape; 5.1 Introduction; 5.2 Computational Models; 5.3 Feedback in the Primate Object Pathway; 5.4 Generative Models of Shape; 5.4.1 Localized Diffeomorphisms: Formlets; 5.5 Formlet Coding; 5.5.1 Formlet Bases; 5.5.2 Diffeomorphism Constraint; 5.5.3 Formlet Composition; 5.6 Formlet Pursuit; 5.7 Evaluation. 5.8 DiscussionReferences; Chapter 6: Two-Dimensional Shape as a Mid-Level Vision Gestalt; 6.1 General Introduction; 6.2 Part I. Contours of Outline Shapes Derived from Everyday Objects; 6.2.1 Introduction; 6.2.2 The Role of Curvature Singularities in Shape Perception; Silhouette and Outline Versions; Salient Points; Straight-Line Versions; Fragmented Versions; Microgenesis of Fragmented Picture Identification; 6.2.3 Conclusion; 6.3 Part II. From Mid- to Lower-Level Vision: Linking Shape Perception to Perceptual Organization; 6.3.1 Introduction; 6.3.2 Conclusion.
Series Title: Advances in computer vision and pattern recognition.

Abstract:

This comprehensive and authoritative text/reference presents a unique, multidisciplinary perspective on Shape Perception in Human and Computer Vision. Rather than focusing purely on the state of the art, the book provides viewpoints from world-class researchers reflecting broadly on the issues that have shaped the field. Drawing upon many years of experience, each contributor discusses the trends followed and the progress made, in addition to identifying the major challenges that still lie ahead. Topics and features: examines each topic from a range of viewpoints, rather than promoting a speci.

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