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Dance Notations and Robot Motion

Overview of attention for book
Cover of 'Dance Notations and Robot Motion'

Table of Contents

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    Book Overview
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    Chapter 1 Towards Behavioral Objects: A Twofold Approach for a System of Notation to Design and Implement Behaviors in Non-anthropomorphic Robotic Artifacts
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    Chapter 2 Laban Movement Analysis and Affective Movement Generation for Robots and Other Near-Living Creatures
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    Chapter 3 Approaches to the Representation of Human Movement: Notation, Animation and Motion Capture
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    Chapter 4 The Problem of Recording Human Motion
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    Chapter 5 MovEngine—Developing a Movement Language for 3D Visualization and Composition of Dance
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    Chapter 6 Bayesian Approaches for Learning of Primitive-Based Compact Representations of Complex Human Activities
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    Chapter 7 Beyond Watching: Action Understanding by Humans and Implications for Motion Planning by Interacting Robots
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    Chapter 8 Challenges for the Animation of Expressive Virtual Characters: The Standpoint of Sign Language and Theatrical Gestures
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    Chapter 9 Task Modelling for Reconstruction and Analysis of Folk Dances
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    Chapter 10 Dynamic Coordination Patterns in Tango Argentino : A Cross-Fertilization of Subjective Explication Methods and Motion Capture
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    Chapter 11 Abstractions for Design-by-Humans of Heterogeneous Behaviors
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    Chapter 12 Dance Notations and Robot Motion
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    Chapter 13 Laban Movement Analysis—Scaffolding Human Movement to Multiply Possibilities and Choices
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    Chapter 14 Benesh Movement Notation for Humanoid Robots?
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    Chapter 15 The Origin of Dance: Evolutionary Significance on Ritualized Movements of Animals
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    Chapter 16 A Worked-Out Experience in Programming Humanoid Robots via the Kinetography Laban
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    Chapter 17 Using Dynamics to Recognize Human Motion
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    Chapter 18 The Effect of Gravity on Perceived Affective Quality of Robot Movement
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    Chapter 19 Applications for Recording and Generating Human Body Motion with Labanotation
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    Chapter 20 Human Motion Tracking by Robots
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Dance Notations and Robot Motion
Published by
Springer International Publishing, January 2016
DOI 10.1007/978-3-319-25739-6
978-3-31-925737-2, 978-3-31-925739-6

Jean-Paul Laumond, Naoko Abe

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 2%
Unknown 54 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 27%
Student > Master 12 22%
Student > Bachelor 5 9%
Researcher 5 9%
Other 3 5%
Other 10 18%
Unknown 5 9%
Readers by discipline Count As %
Engineering 15 27%
Computer Science 8 15%
Design 6 11%
Arts and Humanities 5 9%
Psychology 3 5%
Other 9 16%
Unknown 9 16%