TY - GEN
T1 - Visualizing Improvisation in LuminAI, an AI Partner for Co-Creative Dance
AU - Long, Duri
AU - Liu, Lucas
AU - Gujrania, Swar
AU - Naomi, Cassandra
AU - Magerko, Brian
N1 - Publisher Copyright:
© 2020 Owner/Author.
PY - 2020/7/15
Y1 - 2020/7/15
N2 - LuminAI is an art installation in which participants can improvise movements with an AI dance partner. In this practice work, we will present the LuminAI installation as well as two visualization tools that interactively demonstrate how the LuminAI agent reasons about movement using both bottom-up learned knowledge and top-down domain knowledge. Participants will first be invited to interact with the LuminAI installation, where they can improvise movement with an AI agent projected onto a screen. They can then see how LuminAI learns relationships between gestures by interacting with MoViz, a visualization in which participants can explore the agent's gesture memory and qualitatively compare the efficacy of unsupervised learning algorithms at clustering gestures. Finally, participants will be invited to interact with a third tool, where they can explore how LuminAI applies top-down domain knowledge to gesture reasoning. Participants will be able to interactively explore how LuminAI uses Laban Movement Analysis's conception of Space to analyze learned movements in terms of the geometric properties of Laban's icosahedron and manipulate these properties to transform and generate new movements. The two visualization tools both represent novel approaches to understanding and analyzing improvisational movement in creative domains.
AB - LuminAI is an art installation in which participants can improvise movements with an AI dance partner. In this practice work, we will present the LuminAI installation as well as two visualization tools that interactively demonstrate how the LuminAI agent reasons about movement using both bottom-up learned knowledge and top-down domain knowledge. Participants will first be invited to interact with the LuminAI installation, where they can improvise movement with an AI agent projected onto a screen. They can then see how LuminAI learns relationships between gestures by interacting with MoViz, a visualization in which participants can explore the agent's gesture memory and qualitatively compare the efficacy of unsupervised learning algorithms at clustering gestures. Finally, participants will be invited to interact with a third tool, where they can explore how LuminAI applies top-down domain knowledge to gesture reasoning. Participants will be able to interactively explore how LuminAI uses Laban Movement Analysis's conception of Space to analyze learned movements in terms of the geometric properties of Laban's icosahedron and manipulate these properties to transform and generate new movements. The two visualization tools both represent novel approaches to understanding and analyzing improvisational movement in creative domains.
KW - artificial intelligence
KW - computational creativity
KW - explainable AI
KW - gesture
KW - gesture clustering
KW - Laban movement analysis
KW - motion analysis
KW - movement improvisation
KW - unsupervised learning
KW - visualization
UR - http://www.scopus.com/inward/record.url?scp=85117540146&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85117540146&partnerID=8YFLogxK
U2 - 10.1145/3401956.3404258
DO - 10.1145/3401956.3404258
M3 - Conference contribution
AN - SCOPUS:85117540146
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 7th International Conference on Movement and Computing, MOCO 2020
PB - Association for Computing Machinery
T2 - 7th International Conference on Movement and Computing, MOCO 2020
Y2 - 15 July 2020 through 17 July 2020
ER -