Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective

Shape perception has always been important in vision research, yet it is now attracting more interest than ever before, fueling the need for an interdisciplinary approach that bridges the fields of computer vision and human vision.

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: presents 33 contributions from an international selection of pre-eminent researchers from both the computer vision and human vision communities; examines each topic from a range of viewpoints, rather than promoting a specific paradigm; discusses topics on contours, shape hierarchies, shape grammars, shape priors, and 3D shape inference; reviews issues relating to surfaces, invariants, parts, multiple views, learning, simplicity, shape constancy and shape illusions; addresses concepts from the historically separate disciplines of computer vision and human vision using the same “language” and methods.

This interdisciplinary collection is essential reading for students and researchers seeking to understand the broader landscape of the problem in order to build their expertise on a firm foundation.

1115138725
Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective

Shape perception has always been important in vision research, yet it is now attracting more interest than ever before, fueling the need for an interdisciplinary approach that bridges the fields of computer vision and human vision.

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: presents 33 contributions from an international selection of pre-eminent researchers from both the computer vision and human vision communities; examines each topic from a range of viewpoints, rather than promoting a specific paradigm; discusses topics on contours, shape hierarchies, shape grammars, shape priors, and 3D shape inference; reviews issues relating to surfaces, invariants, parts, multiple views, learning, simplicity, shape constancy and shape illusions; addresses concepts from the historically separate disciplines of computer vision and human vision using the same “language” and methods.

This interdisciplinary collection is essential reading for students and researchers seeking to understand the broader landscape of the problem in order to build their expertise on a firm foundation.

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Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective

Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective

Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective

Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective

eBook2013 (2013)

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Overview

Shape perception has always been important in vision research, yet it is now attracting more interest than ever before, fueling the need for an interdisciplinary approach that bridges the fields of computer vision and human vision.

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: presents 33 contributions from an international selection of pre-eminent researchers from both the computer vision and human vision communities; examines each topic from a range of viewpoints, rather than promoting a specific paradigm; discusses topics on contours, shape hierarchies, shape grammars, shape priors, and 3D shape inference; reviews issues relating to surfaces, invariants, parts, multiple views, learning, simplicity, shape constancy and shape illusions; addresses concepts from the historically separate disciplines of computer vision and human vision using the same “language” and methods.

This interdisciplinary collection is essential reading for students and researchers seeking to understand the broader landscape of the problem in order to build their expertise on a firm foundation.


Product Details

ISBN-13: 9781447151951
Publisher: Springer London
Publication date: 06/29/2013
Series: Advances in Computer Vision and Pattern Recognition
Sold by: Barnes & Noble
Format: eBook
Pages: 502
File size: 9 MB

Table of Contents

The Role of Mid-Level Shape Priors in Perceptual Grouping and Image Abstraction
S.J. Dickinson, A. Levinshtein, P. Sala and C. Sminchisescu

Symmetry is the Sine Qua Non of Shape
Y. Li, T. Sawada, Y. Shi, R.M. Steinman and Z. Pizlo

Flux Graphs for 2D Shape Analysis
M. Rezanejad and K. Siddiqi

An Integrated Bayesian Approach to Shape Representation and Perceptual Organization
J. Feldman, M. Singh, E. Briscoe, V. Froyen, S. Kim and J. Wilder

Perceptual Organization of Shape
J.H. Elder

Two-Dimensional Shape as a Mid-Level Vision Gestalt
J. Wagemans

Shape Priors for Image Segmentation
D. Cremers

Observations on Shape from Shading in Humans
A.J. Schofield, P. Sun and G. Mazzilli

Deformations and Lighting
D. Jacobs, A. Jorstad and A. Trouvé

The Shape of Space
J. Koenderink and A. van Doorn

The Visual Hierarchy Mirage: Seeing Trees in a Graph
S.W. Zucker

Natural Selection and Shape Perception
M. Singh and D.D. Hoffman

Shape as an Emergent Property
I.H. Jemryn

Representing 3D Shape and Location
A. Glennerster

Joint Registration and Shape Analysis of Curves and Surfaces
J. Su, S. Kurtek and A. Srivastava

The Statistics of Shape, and Reflectance, and Lighting in Real-World Scenes
R.F. Murray

Structure vs. Appearance and 3D vs. 2D: A Numeric Answer
W. Hu, Z. Si and S-C. Zhu

Visual Shape Perception and Representation: Bridging Subsymbolic and Symbolic Coding
P.J. Kellman, P. Garrigan and G. Erlikhman

3D Face Reconstruction from Single Two-Tone and Color Images
I. Kemelmacher-Shlizerman, R. Basri and B. Nadler

Perception and Action without Veridical Metric Reconstruction: An Affine Approach
F. Domini and C. Caudek

A Stochastic Grammar for Natural Shapes
P.F. Felzenszwalb

Hard-Wired and Plastic Mechanisms in 3D Shape Perception
Q. Zaidi, A. Li, C. Wong, E. Cohen and X. Meng

Holistic Shape Recognition: Where-To-Look and How-To-Look
J. Shi

Shape Processing as Inherently Three-Dimensional
C.W. Tyler

The Role of Shape in Visual Recognition
B. Ommer

Human Object Recognition: Appearance vs. Shape
I. Biederman

Shape-Based Object Discovery in Images
S. Todorovic and N. Payet

Schema-Driven Influences in Recovering 3D Shape from Motion in Human and Computer Vision
T.V. Papathomas and D. DeCarlo

Detecting, Representing and Attending to Visual Shape
A.J. Rodriguez-Sánchez, G.L. Dudek and J.K. Tsotsos

Toward a Dynamical View of Object Perception
M.A. Peterson and L. Cacciamani

Modeling Shapes with Higher-Order Graphs: Methodology and Applications
C. Wang, Y. Zeng, D. Samaras and N. Paragios

Multisensory Shape Processing
C. Wallraven

Shape-Based Instance Detection under Arbitrary Viewpoint
E. Hsiao and M. Hebert

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