InteractML: Node Based Tool to Empower Artists and Dancers in using Interactive Machine Learning for Designing Movement Interaction
Clarice Hilton, Carlos González Díaz, Ruth Gibson, Phoenix Perry, Rebecca Fiebrink, Michael Zbyszyński, Nicola Plant, Bruno Martelli, Marco Fyfe Pietro Gillies · University of the Arts London Research Online (University of the Arts London) · 2020
Artists, and particularly dancers, have a deep knowledge of movement that can inform movement interaction for immersive media. There are few tools that enable movement interaction in immersive technology to be easily designed by nonprogrammers. We explain the design rationale behind InteractML a node-based interactive machine learning tool for designing movement-based interaction. We also describe a design principle:that the design should serve a dual purpose of increasing understanding of machine learning whilst giving access to customise the machine learning system.