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Learning to dance with a human
conference contribution
posted on 2013-01-01, 00:00 authored by John Mccormick, Kim Vincs, Saeid Nahavandi, Douglas CreightonDouglas CreightonArtificial neural networks are an effective means of allowing software agents to learn about and filter aspects of their domain. In this paper we explore the use of artificial neural networks in the context of dance performance. The software agent’s neural network is presented with movement in the form of motion capture streams, both pre-recorded and live. Learning can be viewed as analogous to rehearsal, recognition and response to performance. The interrelationship between the software agent and dancer throughout the process is considered as a potential means of allowing the agent to function beyond its limited self-contained capability.
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Event
International Symposium of Electronic Art (19th : 2013 : Sydney, N.S.W.)Publisher
ISEA International Australian Network for Art & Technology, University of SydneyLocation
Sydney, N.S.W.Place of publication
Sydney, N.S.W.Start date
2013-06-07End date
2013-06-16Language
engPublication classification
E1 Full written paper - refereed; E Conference publicationCopyright notice
2013, The AuthorsEditor/Contributor(s)
K Cleland, L Fisher, R HarleyTitle of proceedings
ISEA 2013 : Resistance is futile : Proceedings of the 2013 International Symposium on Electronic ArtsUsage metrics
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