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Complex Motion

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Cover of 'Complex Motion'

Table of Contents

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    Book Overview
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    Chapter 1 Optical Flow Estimation from Monogenic Phase
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    Chapter 2 Optimal Filters for Extended Optical Flow
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    Chapter 3 Wiener-Optimized Discrete Filters for Differential Motion Estimation
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    Chapter 4 Boundary Characterization Within the Wedge-Channel Representation
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    Chapter 5 Multiple Motion Estimation Using Channel Matrices
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    Chapter 6 Divide-and-Conquer Strategies for Estimating Multiple Transparent Motions
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    Chapter 7 Towards a Multi-camera Generalization of Brightness Constancy
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    Chapter 8 Complex Motion in Environmental Physics and Live Sciences
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    Chapter 9 Bayesian Approaches to Motion-Based Image and Video Segmentation
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    Chapter 10 On Variational Methods for Fluid Flow Estimation
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    Chapter 11 Motion Based Estimation and Representation of 3D Surfaces and Boundaries
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    Chapter 12 A Probabilistic Formulation of Image Registration
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    Chapter 13 Myocardial Motion and Strain Rate Analysis from Ultrasound Sequences
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    Chapter 14 Determining the Translational Speed of a Camera from Time-Varying Optical Flow
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    Chapter 15 A Robust Approach for Ego-Motion Estimation Using a Mobile Stereo Platform
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    Chapter 16 Robust Monocular Detection of Independent Motion by a Moving Observer
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    Chapter 17 Tracking Complex Objects Using Graphical Object Models
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Mentioned by

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2 Wikipedia pages

Citations

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3 Dimensions

Readers on

mendeley
18 Mendeley
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Title
Complex Motion
Published by
Springer Berlin Heidelberg, May 2007
DOI 10.1007/978-3-540-69866-1
ISBNs
978-3-54-069864-7, 978-3-54-069866-1
Editors

Jähne, Bernd, Mester, Rudolf, Barth, Erhardt, Scharr, Hanno

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 6%
Portugal 1 6%
Unknown 16 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 39%
Student > Master 3 17%
Researcher 3 17%
Professor 2 11%
Professor > Associate Professor 2 11%
Other 1 6%
Readers by discipline Count As %
Computer Science 6 33%
Psychology 3 17%
Neuroscience 3 17%
Engineering 2 11%
Medicine and Dentistry 1 6%
Other 2 11%
Unknown 1 6%