The application of motion-capture technology in telematic and virtual dance performance through a framework for long-distance remote communication

This project involves a unique use-case and experimental exploration of the affordances of new marker-less motion-capture systems such as Perception Neuron and Posenet in the remote creation, rehearsal, teaching, and performance of dance work. Aspects of this are: Affordable and accessible motion-capture technology as a creative tool for choreography Real-time telematic dance communication Remote collaborative devising of dance choreography Online and interactive performance Remote rehearsal of performance Virtual choreography in virtual spaces Choreography with intelligent machines (machine learning) Remote teaching of dance choreography in three dimensions Abstracted generative aesthetic visualisation of dance movement for performance We will deliver: A framework for long-distance remote communication of movement data for dancers (and audio-visual creatives) to practice, rehearse and perform remotely but together. This framework includes: A code template starter-kit for creatives to design a) custom movement visualizations and b) appearances and experiences for virtual performance A controllable interface for online audiences to interact with performances through a digital device A database of movements and gestures that can be used to train movement models for machine-learning-based interactions between dancers and machine software This project addresses an urgent need for useable technology for dance companies to move beyond the limitations of video conferencing platforms. As these companies pivot from touring and the production of new work to other activities, we will make a strong case for the application of time and resources into streams of research into potential futures of choreographic practice that can be digitally shared worldwide.