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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 6: The Importance of the Affective Component of Movement in Action Understanding
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Chapter title
The Importance of the Affective Component of Movement in Action Understanding
Chapter number 6
Book title
Modelling Human Motion
Published by
Springer, Cham, July 2020
DOI 10.1007/978-3-030-46732-6_6
Book ISBNs
978-3-03-046731-9, 978-3-03-046732-6
Authors

Giuseppe Di Cesare

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 17%
Professor > Associate Professor 1 17%
Researcher 1 17%
Student > Master 1 17%
Unknown 2 33%
Readers by discipline Count As %
Engineering 3 50%
Neuroscience 1 17%
Unknown 2 33%