dAnCing LiNes

How do we interpret a multi-participant choreographed performance in the public domain through digital technologies? In collaboration with data visualisation expert David Hunter from University of Colorado at Boulder, and visual artist Zach Duer from Virginia Tech, dAnCing LiNes explores how dance can generate a choreographic view of drawing through mediated representation. In this respect the artwork produced for dAnCing LiNes is not intended as a means of documentation of the live events but as a tool for new artistic production. The intention is to rethink performative drawing beyond the gestural trace of the body in movement through the use of data visualisations. Capturing chorographic scores and task-based instructions through digital technologies, the data visualisations explore how the agency of dance moves from the performative to the visual via technological means by using combinations of established computer vision techniques from OpenCV [1] like Optical Flow, Blob Detection. The visualisations not only reveal the rules of the underlying choreography in each location but also computationally play with and exemplify those rules on a per location basis (five in total).