McCormick, John, Vincs, Kim, Nahavandi, Saeid and Creighton, Douglas 2013, Learning to dance with a human, in ISEA 2013 : Resistance is futile : Proceedings of the 2013 International Symposium on Electronic Arts, ISEA International Australian Network for Art & Technology, University of Sydney, Sydney, N.S.W..
Artificial 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.
Field of Research
190403 Dance 080108 Neural, Evolutionary and Fuzzy Computation 090602 Control Systems, Robotics and Automation
Socio Economic Objective
950105 The Performing Arts (incl. Theatre and Dance) and 970110
Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact email@example.com.