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 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.

The first volume of its kind, covering this important topic from both human and computer vision perspectives Includes contributions from the most preeminent authorities in human and computer vision Though highly interdisciplinary, all contributions share a common language of computational models and methods Includes supplementary material: sn.pub/extras

Klappentext

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.

Dr. Sven Dickinson is Professor and Chair of the Department of Computer Science at the University of Toronto, Canada. Dr. Zygmunt Pizlo is Professor of Mathematical/Computational Cognitive Science in the Department of Psychological Sciences at Purdue University, USA.

Inhalt

The Role of Mid-Level Shape Priors in Perceptual Grouping and Image Abstraction.- Symmetry is the Sine Qua Non of Shape.- Flux Graphs for 2D Shape Analysis.- An Integrated Bayesian Approach to Shape Representation and Perceptual Organization.- Perceptual Organization of Shape.- Two-Dimensional Shape as a Mid-Level Vision Gestalt.- Shape Priors for Image Segmentation.- Observations on Shape from Shading in Humans.- Deformations and Lighting.- The Shape of Space.- The Visual Hierarchy Mirage.- Natural Selection and Shape Perception.- Shape as an Emergent Property.- Representing 3D Shape and Location.- Joint Registration and Shape Analysis of Curves and Surfaces.- The Statistics of Shape, and Reflectance, and Lighting in Real-World Scenes.- Structure vs. Appearance and 3D vs. 2D.- Visual Shape Perception and Representation.- 3D Face Reconstruction from Single Two-Tone and Color Images.- Perception and Action without Veridical Metric Reconstruction.- A Stochastic Grammar for Natural Shapes.- Hard-Wired and Plastic Mechanisms in 3D Shape Perception.- Holistic Shape Recognition.- Shape Processing as Inherently Three-Dimensional.- The Role of Shape in Visual Recognition.- Human Object Recognition.- Shape-Based Object Discovery in Images.- Schema-Driven Influences in Recovering 3D Shape from Motion in Human and Computer Vision.- Detecting, Representing and Attending to Visual Shape.- Toward a Dynamical View of Object Perception.- Modeling Shapes with Higher-Order Graphs: Methodology and Applications.- Multisensory Shape Processing.- Shape-Based Instance Detection under Arbitrary Viewpoint.