Movement Interaction Design for Immersive Media Using Interactive Machine Learning

Plant, Nicola; Gibson, Ruth; Diaz, Carlos Gonzalez; Martelli, Bruno; Zbyszynski, Michael; Fiebrink, Rebecca; Gillies, Marco; Hilton, Clarice and Perry, Phoenix. 2020. 'Movement Interaction Design for Immersive Media Using Interactive Machine Learning'. In: Proceedings of the 7th International Conference on Movement and Computing. Jersey City, NJ, United States 15 – 17 July 2020. [Conference or Workshop Item]

No full text available
[img] Text
Plant et al (2021) Movement Interaction Design_AAM.pdf - Accepted Version
Permissions: Administrator Access Only
Available under License Creative Commons Attribution Non-commercial.

Download (388kB)

Abstract or 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.

Item Type:

Conference or Workshop Item (Other)

Identification Number (DOI):


virtual reality, interaction design, machine learning, immersive media, movement interaction

Departments, Centres and Research Units:



15 July 2020Published

Event Location:

Jersey City, NJ, United States

Date range:

15 – 17 July 2020

Item ID:


Date Deposited:

15 Feb 2021 12:02

Last Modified:

14 Jun 2021 05:22


View statistics for this item...

Edit Record Edit Record (login required)