Teaching a digital performing agent: Artificial neural network and hidden Markov Model for recognising and performing dance movement
McCormick, John, Vincs, Kim, Nahavandi, Saied, Creighton, Douglas, & Hutchison, Stephanie (2014) Teaching a digital performing agent: Artificial neural network and hidden Markov Model for recognising and performing dance movement. In 2014 International Workshop on Movement and Computing (MOCO' 14), 16-17 June 2014, Paris, France.
For a Digital Performing Agent to be able to perform live with a human dancer, it would be useful for the agent to be able to contextualize the movement the dancer is performing and to have a suitable movement vocabulary with which to contribute to the performance. In this paper we will discuss our research into the use of Artificial Neural Networks (ANN) as a means of allowing a software agent to learn a shared vocabulary of movement from a dancer. The agent is able to use the learnt movements to form an internal representation of what the dancer is performing, allowing it to follow the dancer, generate movement sequences based on the dancer's current movement and dance independently of the dancer using a shared movement vocabulary. By combining the ANN with a Hidden Markov Model (HMM) the agent is able to recognize short full body movement phrases and respond when the dancer performs these phrases. We consider the relationship between the dancer and agent as a means of supporting the agent's learning and performance, rather than developing the agent's capability in a self-contained fashion.
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|Item Type:||Conference Paper|
|Keywords:||Artificial Intelligence, Choreographic Agent, Neural Network, Hidden Markov Model, Dance, Recognition|
|Subjects:||Australian and New Zealand Standard Research Classification > STUDIES IN CREATIVE ARTS AND WRITING (190000) > PERFORMING ARTS AND CREATIVE WRITING (190400) > Dance (190403)|
|Divisions:||Current > QUT Faculties and Divisions > Creative Industries Faculty
Past > Schools > School of Media, Entertainment & Creative Arts
|Deposited On:||24 May 2016 22:50|
|Last Modified:||26 May 2016 22:20|
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