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Computational Methods for Theatre Studies? – an online panel series May-July 2022

Juni 29 @ 16:00 - 18:00

Wednesday, 16:00 CET 29.06.2022: Motion & Dance Studies
Peter Broadwell (Stanford Libraries): Deep Learning-Based Pose Estimation for Distant and Close Viewing of Performance Corpora
David Rittershaus (University of Applied Sciences Mainz): Computing Dance Movement: From Manual Annotation to Machine Learning

Organized by Ulf Otto (LMU Munich) and Nora Probst (Univ. of Paderborn)
Machine learning technologies can handle increasingly large amounts of text, image, or video data and have resulted in innovative research strategies in neighboring disciplines that can potentially facilitate new perspectives for Theatre Studies as well.
With this series of five panels, we want to complement the existing Digital Humanities research in Theatre Studies on data models, repertoire data and agent networks with questions about the potentials and politics of computational methods for theater research.
We are particularly interested in having a vivid discussion on the potentials and challenges of computational methods for research into theater and performance, as well as the epistemological politics inevitably involved. On the one hand, we hope that this will add to the ongoing debate on re-positioning Theater Studies within digital (research) cultures and, on the other hand, that it will strengthen the interdisciplinary dialogue.


Juni 29
16:00 - 18:00


Digital via Zoom

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