KinoAI et le carnet audiovisuel : une solution plurielle pour l’étude des répétitions - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue European Journal of Theatre and Performance Année : 2020

KinoAI and the audiovisual notebook : a plural solution for rehearsal studies

KinoAI et le carnet audiovisuel : une solution plurielle pour l’étude des répétitions

Résumé

The ever-growing production of video traces of theatrical work, is both an opportunity and a challenge for researchers in performing art studies. In this communication, we report on the work of an interdisciplinary team of computer scientists, performing art researchers and stage and video artists, towards the common goal of transforming raw video recordings of theatre rehearsals into meaningful movie narratives. Our prototype system, KinoAI, combines sophisticated artificial intelligence techniques with a careful dramaturgic analysis of the rehearsals. We present extensive field experiments and propose new research directions.
KinoAI et le carnet audiovisuel : une solution plurielle pour l'étude des répétitions The ever-growing production of video traces of theatrical work, is both an opportunity and a challenge for researchers in performing art studies. In this communication, we report on the work of an interdisciplinary team of computer scientists, performing art researchers and stage and video artists, towards the common goal of transforming raw video recordings of theatre rehearsals into meaningful movie narratives. Our prototype system, KinoAI, combines sophisticated artificial intelligence techniques with a careful dramaturgic analysis of the rehearsals. We present extensive field experiments and propose new research directions.
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Dates et versions

hal-02797350 , version 1 (05-06-2020)

Identifiants

  • HAL Id : hal-02797350 , version 1

Citer

Rémi Ronfard, Julie Valéro. KinoAI et le carnet audiovisuel : une solution plurielle pour l’étude des répétitions. European Journal of Theatre and Performance, 2020, 2, pp.334-375. ⟨hal-02797350⟩
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