Artificial intelligence for content and context metadata retrieval in photographs and image groups

Peter Fornaro and Vera Chiquet
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Peter Fornaro: University of Basel, Digital Humanities Lab, Switzerland
Vera Chiquet: University of Basel, Digital Humanities Lab, Switzerland

Journal of Digital Media Management, 2021, vol. 9, issue 4, 297-304

Abstract: Cataloguing is a frequent bottleneck in the digitisation of analogue images as it is impossible to scale the necessary content-related knowledge. As this paper discusses, however, it is possible to use well-trained artificial intelligence to semi-automate metadata enhancement for photographic collections. The paper describes a study in which participants indexed historical collections of photographs. In a subsequent interdisciplinary project with contributions from cultural anthropologists, computer scientists, digital humanities researchers and art historians, these descriptions and indexes were then used to train machine-learning components. With this interdisciplinary approach, it is hoped that cataloguing practices can be enhanced, generating new insights into AI and semantic metadata.

Keywords: Machine learning; analogue and digital photography; cultural heritage; semantic metadata; cbir; iiif; curation (search for similar items in EconPapers)
JEL-codes: M11 M15 (search for similar items in EconPapers)
Date: 2021
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