8-11 September 2017, Kulturhaus Kienberg, Switzerland
Jointly organized by ICST and IRCAM
The workshop was a meeting of a small group of researchers and artists collaborating on the topic of movement analysis/interpretation using technological and conceptual approaches. The overall goal was to jointly work through shared concepts and approaches, to evaluate specific technological implementations, and to formulate strategies for future developments and possible projects.
The workshop brought together two academic research groups, the IMM team of the Institue for Computer Music and Sound Technology (ICST) at the Zurich University of the Arts (ZHdK), and the ISMM team of IRCAM (Paris, France), with selected invited researchers and artists. As both group developed similar tools for movement analysis, the workshop allowed for discussing the following works currently developed at both institutions.
The ICST team (University of the Arts – Zürich) evaluated the workflow developed with the Machine Learning Toolset and the possibilities for future directions and necessary expansions (algorithms and interfaces) to increase its flexibility and interoperability.
The IRCAM team questioned current issues in movement technology for mediated interaction. In particular, they evaluated the networked movement recognition tools developed in the Rapid-Mix project.
Bringing together the different expertise of the group, methodological questions were addressed about cognitive and technological aspects of movement analysis research and concrete steps for larger project collaborations. Further was addressed on a theoretical level the fundamental topic of the dancer’s self-perception and possible approaches to (machine-) identification of general as well as idiosyncratic movement qualities.
The format of the workshop was that of the retreat: a group of ten people spent up to four days collaborating. The activities comprised general discussions, smaller workgroup sessions, experimental/evaluation sessions and showings/discussions of findings.