Rich state transitions in a media choreography framework using an idealized model of cloud dynamics

Brandon Mechtley, Julian Stein, Christopher Roberts, Sha Xin Wei

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

1 Scopus citations

Abstract

This paper presents An Experiential Model of the Atmosphere, a responsive media environment including multi-surface video projection and ambisonic audio feedback in which participants can fluidly interact with an idealized model of atmospheric dynamics, using the presence and motion of their bodies to force convection, condense and evaporate moisture, and manipulate atmospheric pressure gradients.We use this model to explore steering of computational models of complex systems that can span gamuts of single to multi-body interaction, local to global spatial scales, short-to long-term time scales, and abstract representations to immersive, felt environments.

Original languageEnglish (US)
Title of host publicationThematic Workshops 2017 - Proceedings of the Thematic Workshops of ACM Multimedia 2017, co-located with MM 2017
PublisherAssociation for Computing Machinery, Inc
Pages477-484
Number of pages8
ISBN (Electronic)9781450354165
DOIs
StatePublished - Oct 23 2017
Event1st International ACM Thematic Workshops, Thematic Workshops 2017 - Mountain View, United States
Duration: Oct 23 2017Oct 27 2017

Other

Other1st International ACM Thematic Workshops, Thematic Workshops 2017
CountryUnited States
CityMountain View
Period10/23/1710/27/17

Keywords

  • Dense media
  • Media choreography
  • Steerable simulation

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Theory and Mathematics
  • Theoretical Computer Science

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    Mechtley, B., Stein, J., Roberts, C., & Wei, S. X. (2017). Rich state transitions in a media choreography framework using an idealized model of cloud dynamics. In Thematic Workshops 2017 - Proceedings of the Thematic Workshops of ACM Multimedia 2017, co-located with MM 2017 (pp. 477-484). Association for Computing Machinery, Inc. https://doi.org/10.1145/3126686.3126771