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Puppeteering an AI - Interactive Control of a Machine-Learning based Artificial Dancer

  • This paper describes the authors' first experiments in creating an artificial dancer whose movements are generated through a combination of algorithmic and interactive techniques with machine learning. This approach is inspired by the time honoured practice of puppeteering. In puppeteering, an articulated but inanimate object seemingly comes to live through the combined effects of a humanThis paper describes the authors' first experiments in creating an artificial dancer whose movements are generated through a combination of algorithmic and interactive techniques with machine learning. This approach is inspired by the time honoured practice of puppeteering. In puppeteering, an articulated but inanimate object seemingly comes to live through the combined effects of a human controlling select limbs of a puppet while the rest of the puppet's body moves according to gravity and mechanics. In the approach described here, the puppet is a machine-learning-based artificial character that has been trained on motion capture recordings of a human dancer. A single limb of this character is controlled either manually or algorithmically while the machine-learning system takes over the role of physics in controlling the remainder of the character's body. But rather than imitating physics, the machine-learning system generates body movements that are reminiscent of the particular style and technique of the dancer who was originally recorded for acquiring training data. More specifically, the machine-learning system operates by searching for body movements that are not only similar to the training material but that it also considers compatible with the externally controlled limb. As a result, the character playing the role of a puppet is no longer passively responding to the puppeteer but makes movement decisions on its own. This form of puppeteering establishes a form of dialogue between puppeteer and puppet in which both improvise together, and in which the puppet exhibits some of the creative idiosyncrasies of the original human dancer.show moreshow less

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Metadaten
Document Type:Conference Proceeding
Conference Type:Konferenzartikel
Zitierlink: https://opus.hs-offenburg.de/8628
Bibliografische Angaben
Title (English):Puppeteering an AI - Interactive Control of a Machine-Learning based Artificial Dancer
Conference:Generative Art Conference (24. : 15th-17th of December 2021 : Cagliari, Sardinia, Italy/online)
Author:Daniel Bisig, Ephraim WegnerStaff Member
Year of Publication:2021
Place of publication:Rom
Publisher:Domus Argenia Publisher
First Page:315
Last Page:332
Parent Title (English):XXIV Generative Art 2021 : proceedings of XXIV GA conference
Editor:Celestino Soddu, Enrica Colabella
ISBN:978-88-96610-43-5
URL:http://www.artscience-ebookshop.com/GA2021_proceedings_web.pdf
Language:English
Inhaltliche Informationen
Institutes:Fakultät Medien (M) (ab 22.04.2021)
Institutes:Bibliografie
Tag:artificial dancer; dance and technology; deep learning; motion synthesis
Formale Angaben
Open Access: Open Access 
 Bronze 
Licence (German):License LogoCreative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell - Weitergabe unter gleichen Bedingungen 4.0 International