Visualizing Improvisation in LuminAI, an AI Partner for Co-Creative Dance

Duri Long, Lucas Liu, Swar Gujrania, Cassandra Naomi, Brian Magerko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 7th International Conference on Movement and Computing, MOCO 2020
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450375054
DOIs
StatePublished - Jul 15 2020
Event7th International Conference on Movement and Computing, MOCO 2020 - Jersey City, Virtual, United States
Duration: Jul 15 2020Jul 17 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference7th International Conference on Movement and Computing, MOCO 2020
Country/TerritoryUnited States
CityJersey City, Virtual
Period7/15/207/17/20

Keywords

  • artificial intelligence
  • computational creativity
  • explainable AI
  • gesture
  • gesture clustering
  • Laban movement analysis
  • motion analysis
  • movement improvisation
  • unsupervised learning
  • visualization

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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