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Shape Perception in Human and Computer Vision

ACVPR: SHAPE PERCEPTION IN HUMAN AND COMPUTER VISION

Information Technology

Computing & Information Technology

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B2B GT

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B2B & B2C

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.

POST SECONDARY FOUR YEAR

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Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Half Title Page.
Other Frontmatter.
Title Page.
Copyright Page.
Dedication.
Preface.
Contents.
Contributors.
1: The Role of Mid-Level Shape Priors in Perceptual Grouping and Image Abstraction.
2: Symmetry Is the Sine Qua Non of Shape.
3: Flux Graphs for 2D Shape Analysis.
4: An Integrated Bayesian Approach to Shape Representation and Perceptual Organization.
5: Perceptual Organization of Shape.
6: Two-Dimensional Shape as a Mid-Level Vision Gestalt.
7: Shape Priors for Image Segmentation.
8: Observations on Shape-from-Shading in Humans.
9: Deformations and Lighting.
10: The Shape of Space.
11: The Visual Hierarchy Mirage: Seeing Trees in a Graph.
12: Natural Selection and Shape Perception.
13: Shape as an Emergent Property.
14: Representing 3D Shape and Location.
15: Joint Registration and Shape Analysis of Curves and Surfaces.
16: The Statistics of Shape, Reflectance, and Lighting in Real-World Scenes.
17: Structure vs. Appearance and 3D vs. 2D? A Numeric Answer.
18: Challenges in Understanding Visual Shape Perception and Representation: Bridging Subsymbolic and Symbolic Coding.
19: 3D Face Reconstruction from Single Two-Tone and Color Images.
20: Perception and Action Without Veridical Metric Reconstruction: An Affine Approach.
21: A Stochastic Grammar for Natural Shapes.
22: Hard-Wired and Plastic Mechanisms in 3-D Shape Perception.
23: Holistic Shape Recognition: Where-to-Look and How-to-Look.
24: Shape Processing as Inherently Three-Dimensional.
25: The Role of Shape in Visual Recognition.
26: Human Object Recognition: Appearance vs. Shape.
27: Shape-Based Object Discovery in Images.
28: Schema-Driven Influences in Recovering 3-D Shape from Motion in Human and Computer Vision.
29: Detecting, Representing and Attending to Visual Shape.
30: Toward a Dynamical View of Object Perception.
31: Modeling Shapes with Higher-Order Graphs: Methodology and Applications.
32: Multisensory Shape Processing.
33: Shape-Based Instance Detection under Arbitrary Viewpoint.
Index.

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Shape Perception in Human and Computer Vision