Published June 30, 2023 | Version v1
Conference paper Open

AI-Assisted Performance Analysis: Deep Learning for Live and Archival Theater

  • 1. Stanford University, United States of America
  • 1. University of Graz
  • 2. Belgrade Center for Digital Humanities
  • 3. Le Mans Université
  • 4. Digital Humanities im deutschsprachigen Raum

Description

This project explores computational uses of pose analysis to investigate questions of directorial style and actorly interpretation in theatrical performances. The process involves developing methods to help performing arts scholars and professionals use pose-data models to capture movement from performances, as well as record, analyze, recreate and remix those movements.

Files

BROADWELL_Peter_AI_Assisted_Performance_Analysis__Deep_Learn.pdf

Additional details

Related works

Is part of
Book: 10.5281/zenodo.7961822 (DOI)
Is supplemented by
Poster: 10.5281/zenodo.8228553 (DOI)