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GaussBox is a pedagogical tool for prototyping movement interaction using machine learning. GaussBox proposes novel, interactive visualizations that expose the behavior and internal values of probabilistic models rather than their sole results. Such visualizations have both pedagogical and creative potentials to guide users in the exploration, experience and craft of machine learning for interaction design.


Gaussbox principle



GaussBox will be available **sometime** as an open-source application. Gaussbox supports several types of input devices (mouse, Leap Motion, Myo, OSC). It allows for playing with both real-time recognition and continuous mapping to sound (with CataRT-style sound synthesis or OSC).


  • “GaussBox: Prototyping Movement Interaction with Interactive Visualizations of Machine Learning,” Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '16) , San Jose, CA, ACM, , pp. 3667--3670. DOI: 10.1145/2851581.2890257.
  • “Supporting User Interaction with Machine Learning through Interactive Visualizations,” CHI'16 Workshop on Human-Centred Machine Learning , San Jose, CA, . URL: