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Theoretical foundations of computer vision

Overview of attention for book
Cover of 'Theoretical foundations of computer vision'

Table of Contents

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    Book Overview
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    Chapter 1 Attentive Visual Motion Processing: Computations in the Log-Polar Plane
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    Chapter 2 Invariant Thinning and Distance Transform
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    Chapter 3 Recognition of Images Degraded by Linear Motion Blur without Restoration
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    Chapter 4 Symmetric Bi- and Trinocular Stereo: Tradeoffs between Theoretical Foundations and Heuristics
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    Chapter 5 Surface from Motion—without and with Calibration
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    Chapter 6 Properties of Pyramidal Representations
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    Chapter 7 A Robust Approach to Estimation of Parametric Models
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    Chapter 8 Computer Vision and Mathematical Morphology
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    Chapter 9 A Variational Approach to the Design of Early Vision Algorithms
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    Chapter 10 Banach Constructor and Image Compression
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    Chapter 11 Piecewise Linear Approximation of Planar Jordan Curves and Arcs: Theory and Applications
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    Chapter 12 Segmentation with Volumetric Part Models
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    Chapter 13 Theoretical Foundations of Anisotropic Diffusion in Image Processing
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    Chapter 14 Stability and Likelihood of Views of Three Dimensional Objects
Attention for Chapter 12: Segmentation with Volumetric Part Models
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Chapter title
Segmentation with Volumetric Part Models
Chapter number 12
Book title
Theoretical Foundations of Computer Vision
Published by
Springer, Vienna, January 1996
DOI 10.1007/978-3-7091-6586-7_12
Book ISBNs
978-3-21-182730-7, 978-3-70-916586-7
Authors

F. Solina, Solina, F.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 100%
Readers by discipline Count As %
Engineering 1 100%

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