Movement interaction design for immersive media using interactive machine learning

Tools

Plant, Nicola and Gibson, Ruth and Gonzalez Diaz, Carlos and Martelli, Bruno and Zbyszynski, Michael and Fiebrink, Rebecca and Gillies, Marco and Hilton, Clarice and Perry, Phoenix (2020) Movement interaction design for immersive media using interactive machine learning. In: 7th International Conference on Movement and Computing (MOCO '20), 15-17 July 2020, Online.

Type of Research:	Conference, Symposium or Workshop Item
Creators:	Plant, Nicola and Gibson, Ruth and Gonzalez Diaz, Carlos and Martelli, Bruno and Zbyszynski, Michael and Fiebrink, Rebecca and Gillies, Marco and Hilton, Clarice and Perry, Phoenix
Description:	Interactive Machine Learning is a promising approach for designing movement interaction because it allows developers to capture complex movements by simply performing them. We introduce a new tool being developed to make embodied interaction design faster, adaptable and accessible to developers of varying experience and background. Using the tool, we conduct workshops with creative practitioners and developers to explore techniques that equip users with embodied ideation design strategies encouraging full body interaction for immersive media.
Official Website:	https://moco20.movementcomputing.org/program
Keywords/subjects not otherwise listed:	movement interaction, machine learning, immersive media, interaction design, virtual reality
Your affiliations with UAL:	Research Centres/Networks > Institute for Creative Computing
Date:	17 July 2020
Funders:	Engineering and Physical Sciences Research Council
Related Websites:	https://interactml.com/
Related Websites:	Organisation
Event Location:	Online
Date Deposited:	22 Feb 2021 11:06
Last Modified:	22 Feb 2021 11:06
Item ID:	16503
URI:	https://ualresearchonline.arts.ac.uk/id/eprint/16503

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