Interactive Machine Learning offers a method for designing movement interaction that supports creators in implementing even complex movement designs in their immersive applications by simply performing them with their bodies. We introduce a new tool, In-teractML, and an accompanying ideation method, which makes movement interaction design faster, adaptable and accessible to creators of varying experience and backgrounds, such as artists, dancers and independent game developers. The tool is specifically tailored to non-experts as creators configure and train machine learning models via a node-based graph and VR interface, requiring minimal programming. We aim to democratise machine learning for movement interaction to be used in the development of a range of creative and immersive applications. CCS CONCEPTS• Human-centered computing → Interaction design; Human computer interaction (HCI).

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 In-teractML.

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This research is a collaboration with Aardman Animations, a worldrenowned animation studio to innovate their linear storytelling into a real-time, interactive and spatially immersive experience. We developed a room-scale VR experience to simulate the installation in order to visualise the projection distortion under different conditions. A study was then conducted using our simulation to investigate the effect of distortion of the projections on the experience of immersion and how three factors effected the distortion. This paper explains the preliminary results and the process.