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This paper presents the design and implementation of a software platform for creating interactive visualisations that respond to the free-form movements of a non-professional dancer. The visualisations can be trained to respond to the idiosyncratic movements of an individual dancer. This adaptive process is controlled by Interactive Machine Learning. Our approach is novel because the behaviour of the interactive visualisations is trained by a dancer dancing, rather than a computer scientist explicitly programming rules. In this way IML enables an 'embodied' form of design, where a dancer can design an interactive system by moving, rather than by analysing movement. This embodied design process taps into and supports our natural and embodied human understanding of movement.
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Stored only when both papers are in the corpus — 14 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.