Machine Intelligence for Motion Exegesis (MIME): Applying Pose Estimation and Related Technologies to Analyze Archival Performance Recordings

Michael Rau is a live performance director specializing in new plays, opera, and digital media projects. He has worked internationally in Germany, Brazil, the UK, Ireland, Canada, and the Czech Republic. He has created work in New York City at Lincoln Center, The Public Theater, PS122, HERE Arts Center, Ars Nova, The Bushwick Starr, The Brick, 59E59, 3LD, and Dixon Place. Regionally, his work as been seen at the Ingenuity Festival in Cleveland, OH, and the American Repertory Theatre in Cambridge, MA. He has developed new plays at the Eugene O’Neill National Playwrights Conference, the Lark and the Kennedy Center. Michael Rau is a recipient of fellowships from the Likhachev Foundation, the Kennedy Center, and the National New Play Network. He has been a resident artist at the Orchard Project, E|MERGE, and the Tribeca Performing Arts Center. He has been an associate director for Anne Bogart, Les Waters, Robert Woodruff, and Ivo Van Hove. He is a New York Theater Workshop Usual Suspect and a professor of directing and devising at Stanford University.

Peter Broadwell is a Digital Scholarship Research Developer at the Stanford University Libraries’ Center for Interdisciplinary Digital Research, where his work applies machine learning, web-based visualization, and other methods of digital analysis to complex cultural data. He has a Ph.D. in Musicology from the University of California, Los Angeles and an M.S. degree in Computer Science from the University of California, Berkeley. Recent studies in which he has participated have involved automatic translation and indexing of folklore collections in multiple languages, deep learning-based analysis of dance choreography on social media, and multimedia annotation of Japanese Noh theater performances.