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Taylor Impersonation of AI for Audiovisual Content Documentation and Search

Beteiligte Autor*innen der JOANNEUM RESEARCH:
Editor*innen:
DangNguyen, DucTien and Gurrin, Cathal and Larson, Martha and Smeaton, Alan F. and Rudinac, Stevan and Dao, MinhSon and Trattner, Christoph and Chen, Phoebe
Autor*innen:
Victor Adriel de Jesus Oliveira and Gernot Rottermanner and Magdalena Boucher and Stefanie Größbacher and Peter Judmaier and Werner Bailer and Georg Thallinger and Thomas Kurz and Jakob Frank and Christoph Bauer and Gabriele Fröschl and Michael Batlogg
Abstract:
While AI-based audiovisual analysis tools have without doubt made huge progress, integrating them in media production and archiving workflows is still challenging, as the provided annotations may not match needs in terms of type, granularity and accuracy of metadata, and do not well align with existing workflows. We propose a system for annotation and search in media archive applications, using a range of AI-based analysis methods. In order to facilitate communication of explanations and collect relevance feedback, an impersonation of the systemstextquoteright intelligence, named Taylor, is included as an element of the user interface.
Titel:
Taylor Impersonation of AI for Audiovisual Content Documentation and Search
Herausgeber (Verlag):
Springer Nature Switzerland
Seiten:
751-757
ISBN
9783031278181

Publikationsreihe

Buchtitel
MultiMedia Modeling
Herausgeber(Verlag)
Springer Nature Switzerland
Adresse
Cham
ISSN
16113349

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