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Modelling Human Motion

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Cover of 'Modelling Human Motion'

Table of Contents

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    Book Overview
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    Chapter 1 Modeling Human Motion: A Task at the Crossroads of Neuroscience, Computer Vision and Robotics
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    Chapter 2 The Neurophysiology of Action Perception
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    Chapter 3 Beyond Automatic Motor Mapping: New Insights into Top-Down Modulations on Action Perception
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    Chapter 4 The Visual Perception of Biological Motion in Adults
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    Chapter 5 The Development of Action Perception
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    Chapter 6 The Importance of the Affective Component of Movement in Action Understanding
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    Chapter 7 Optical Flow Estimation in the Deep Learning Age
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    Chapter 8 Spatio-Temporal Action Instance Segmentation and Localisation
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    Chapter 9 Vision During Action: Extracting Contact and Motion from Manipulation Videos—Toward Parsing Human Activity
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    Chapter 10 Human Action Recognition and Assessment Via Deep Neural Network Self-Organization
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    Chapter 11 Movement Expressivity Analysis: From Theory to Computation
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    Chapter 12 The Practice of Animation in Robotics
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    Chapter 13 Adapting Movements and Behaviour to Favour Communication in Human-Robot Interaction
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    Chapter 14 Expressivity Comes First, Movement Follows: Embodied Interaction as Intrinsically Expressive Driver of Robot Behaviour
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    Chapter 15 Gestures in Educational Behavior Coordination. Grounding an Enactive Robot-Assisted Approach to Didactics
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    Chapter 16 Priming and Timing in Human-Robot Interactions
Attention for Chapter 7: Optical Flow Estimation in the Deep Learning Age
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Citations

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118 Mendeley
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Chapter title
Optical Flow Estimation in the Deep Learning Age
Chapter number 7
Book title
Modelling Human Motion
Published by
Springer, Cham, July 2020
DOI 10.1007/978-3-030-46732-6_7
Book ISBNs
978-3-03-046731-9, 978-3-03-046732-6
Authors

Junhwa Hur, Stefan Roth

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 118 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 24 20%
Student > Ph. D. Student 23 19%
Researcher 13 11%
Student > Bachelor 8 7%
Student > Doctoral Student 4 3%
Other 10 8%
Unknown 36 31%
Readers by discipline Count As %
Computer Science 36 31%
Engineering 28 24%
Agricultural and Biological Sciences 2 2%
Biochemistry, Genetics and Molecular Biology 1 <1%
Business, Management and Accounting 1 <1%
Other 7 6%
Unknown 43 36%