Univesité Rennes 2
DATE 09-02-2023 DURÉE 00:33:21 GENRE Conférence PUBLIC Tous publics DISCIPLINE Architecture et art du paysage, Arts visuels et plastiques, Histoire de l'art, Cinéma, Danse, Musique, Théâtre, Informatique appliquée Producteur Université Rennes 2


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

Michael Rau and Peter Broadwell, Stanford University (USA)

MIME is a collaborative effort between faculty in the Department of Theater and Performance Studies at Stanford University and developers at the Stanford Libraries’ Center for Interdisciplinary Digital Research. The project incorporates a suite of software tools for applying deep learning-based pose and gesture estimation to recorded theatrical performances, coupled with a database-backed web interface to facilitate close evaluation and refinement of data inputs and analytical outputs via interactive visualizations and built-in code notebooks. Previously unexplored, computationally oriented research inquiries in performance studies drive the collaboration; these include characterization of the range of choreographed poses within a performance, tracking the evolution of actors’ embodiment of a role, and comparative thematic and stylistic analysis of performances.

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.