EmViz: Expressing Movement Qualities

FlowFlow was an improvised dance performance at the User in Flux workshop at the 2011 ACM CHI Conference on Human Factors in Computing Systems. Movement qualities are extracted in real time from the performer’s body using EffortDetect. EffortDetect is a real-time machine-learning system that applies Laban Movement Analysis, a rigorous framework for analyzing the human movement, to extract movement qualities from a moving body in the form of Laban Basic Efforts. It produces a dynamic stream of Laban Basic Effort qualities in real time. We extended the use of EffortDetect by designing a visualization system that uses movement quality parameters to generate an abstract visualization for use in dance performance. [Program PDF]


Subyen, P., Maranan, D., Carlson, K., Schiphorst, T., Pasquier, P. ‘Flow: Expressing Movement Quality’, CHI 2011 Workshop: The user in flux: bringing HCI and digital arts together to interrogate shifting roles in interactive media, Vancouver, BC, Canada, May 2011.