Interactive Machine Learning for Embodied Interaction Design: A tool and methodology

Ruth Gibson, Nicola Plant, Clarice Hilton, Marco Gillies, Rebecca Fiebrink, Phoenix Perry, Carlos Gonzalez Diaz, Bruno Martelli, Michael Zbyszynski

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

Abstract

As immersive technologies are increasingly being adopted by artists, dancers and developers in their creative work, there is a demand for tools and methods to design compelling ways of embodied interaction within virtual environments. Interactive Machine Learning allows creators to quickly and easily implement movement interaction in their applications by performing examples of movement to train a machine learning model. A key aspect of this training is providing appropriate movement data features for a machine learning model to accurately characterise the movement then recognise it from incoming data. We explore methodologies that aim to support creators’ understanding of movement feature data in relation to machine learning models and ask how these models hold the potential to inform creators’ understanding of their own movement. We propose a 5-day hackathon, bringing together artists, dancers and designers, to explore designing movement interaction and create prototypes using new interactive machine learning tool InteractML.
Original languageEnglish
Title of host publicationProceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction
Pages1-5
Number of pages5
ISBN (Electronic)9781450382137
DOIs
Publication statusPublished - 14 Feb 2021
Event15th ACM International Conference on Tangible, Embedded and Embodied Interaction - Online
Duration: 14 Feb 202119 Feb 2021
https://tei.acm.org/2021/

Publication series

NameTEI 2021 - Proceedings of the 15th International Conference on Tangible, Embedded, and Embodied Interaction

Conference

Conference15th ACM International Conference on Tangible, Embedded and Embodied Interaction
Abbreviated titleTEI 2021
Period14/02/2119/02/21
Internet address

Bibliographical note

Free online to read

Keywords

  • Artificial intelligence
  • Machine learning
  • Bodystorming
  • Movement
  • Gesture
  • Hackathon
  • HCI
  • Tool
  • immersive media
  • movement interaction
  • performance
  • interactive machine learning

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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