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Cover image for Computer vision : from surfaces to 3D objects
Title:
Computer vision : from surfaces to 3D objects
Publication Information:
Boca Raton, FL : Chapman and Hall/CRC, c2011.
Physical Description:
xxvi, 250 p. : ill. (some col.) ; 25 cm.
ISBN:
9781439817124
Subject Term:
Added Author:

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30000010274716 TA1634 C657 2011 Open Access Book Book
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30000003499484 TA1634 .C657 2011 Open Access Book Book
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Summary

Summary

The typical computational approach to object understanding derives shape information from the 2D outline of the objects. For complex object structures, however, such a planar approach cannot determine object shape; the structural edges have to be encoded in terms of their full 3D spatial configuration. Computer Vision: From Surfaces to 3D Objects is the first book to take a full approach to the challenging issue of veridical 3D object representation. It introduces mathematical and conceptual advances that offer an unprecedented framework for analyzing the complex scene structure of the world.

An Unprecedented Framework for Complex Object Representation
Presenting the material from both computational and neural implementation perspectives, the book covers novel analytic techniques for all levels of the surface representation problem. The cutting-edge contributions in this work run the gamut from the basic issue of the ground plane for surface estimation through mid-level analyses of surface segmentation processes to complex Riemannian space methods for representing and evaluating surfaces.

State-of-the-Art 3D Surface and Object Representation
This well-illustrated book takes a fresh look at the issue of 3D object representation. It provides a comprehensive survey of current approaches to the computational reconstruction of surface structure in the visual scene.


Author Notes

Christopher W. Tyler is the director of the Brain Imaging Center at the Smith-Kettlewell Eye Research Institute. His current research encompasses brain imaging studies and mathematical modeling of the mechanisms of human stereoscopic depth, motion, and face perception as well as higher cognitive processing. He and his team have developed new methods to determine the dynamics of the neural population responses underlying brain imaging signals. By designing stimuli to probe specific neural sub-populations, this new methodology can be used to explore neural properties in the human brain and the changes in neural dynamics during the learning process.


Table of Contents

Brian Potetz and Tai Sing LeeAjay Mishra and Yiannis AloimonosJames CouchlanWei Zeng and Feng Luo and Shing-Tung Yau and David Xianfeng GuVolodymyr V. IvanchenkoTadamasa Sawada and Yunfeng Li and Zygmunt PizloAlessandro Sarti and Giovanna CittiRüdiger Von Der HeydtChristopher W. Tyler and Lora T. LikovaPhilip J. Kellman and Patrick Garrigan and Evan M. PalmerJames T. Todd
Introduction: The Role of Midlevel Surface Representation in 3D Object Encodingp. vii
Contributorsp. xxv
Chapter 1 Scene Statistics and 3D Surface Perceptionp. 1
Chapter 2 Active Segmentation: A New Approachp. 25
Chapter 3 Mechanisms for Propagating Surface Information in 3D Reconstructionp. 51
Chapter 4 3D Surface Representation Using Ricci Flowp. 65
Chapter 5 Cue Interpretation and Propagation: Flat versus Nonflat Visual Surfacesp. 95
Chapter 6 Symmetry, Shape, Surfaces, and Objectsp. 113
Chapter 7 Noncommutative Field Theory in the Visual Cortexp. 125
Chapter 8 Contour-, Surface-, and Object-Related Coding in the Visual Cortexp. 145
Chapter 9 Visual Surface Encoding: A Neuroanalytic Approachp. 163
Chapter 10 3D and Spatiotemporal Interpolation in Object and Surface Formationp. 183
Chapter 11 The Perceptual Representation of the 3D Shapep. 209
Referencesp. 219
Indexp. 241
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