Dancing in data: Representation, repetition and recreation
Hansen, Lise Amy
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This paper describes a new project ‘Dancing in data’. The project examines the potential of computer vision and machine learning to generate novel person-centred, choreographic techniques for processing kinesthetic sensory stimuli. Literature from several fields – philosophy, phenomenology, neuroscience, somatics, performance studies - position the human body as an active agent in learning and making sense of the word, whereby the touching, moving and thinking body can be experienced as sensate and dynamic beyond function. This idea has inspired researchers to consider how bodily interaction may be explored as a method of investigating the transformative alchemy between bodies and technologies.
Movementis: Brain, Body, Cognition;
Keay-Bright, W and Hansen, L.A. (2017) 'Dancing in data: Representation, repetition and recreation' Movementis: Brain, Body, Cognition. Oxford, July 2017
Paper presented at inaugural Movementis Conference at Oxford University in July 2017.