The Dance Tech Collective

Thank you to all who attended last week’s DTC workshop! 💫

Additional thanks to our thoughtful instructors @lisajamhoury & @seestrawrun and NYU Tandon at The Yard @idmnyu for the incredible space and technical support.

Highlights for us:

*Group play with sensors! We worked with 3 volunteer performers in motion capture suits, while additional participants were invited to play with “rigid bodies” (sensor tracked objects, as opposed to the suits’ flexible, free flowing tracking). This led to interactive play where artists could become light sources, steer the camera’s point of view, and more.

*Learning about how Lisa integrates storytelling into her work, specifically in her piece “Maquette.” This live performance explores the human individuality we risk losing in the rapid virtualization of everyday life. The work was partially inspired by the unsettling story of “Norma,” a statue created in the 1940s to represent the average woman, though modeled only after white women ages 21–25, excluding most women by age, race, and body type. “Maquette” explores the notion of averaging, a mechanism used in software and machine learning that has been shown to make false assumptions about individuals, especially regarding neurodiversity, race, and gender.

*For the workshop, the DTC researched various mo-cap systems and more specifically how/if AI is integrated into the OptiTrack → Unreal Engine workflow. The gist for curious minds: there are AI options in Unreal Engine, but the user can choose if they want to opt in. The standard OptiTrack → Unreal workflow does not require/use generative AI or AI assisted tracking to function. DM us if you’d like to learn about other mo-cap systems we’re researching and things we’re considering when approaching these systems.

📸 by @canigetawhitney
Whitney Browne

Additional thanks to @winslowturnerporteriii and @cinemaryann 🪩