Paintings by Artificial Intelligence. Large-scale search for visual similarities,
Isabella di Lenardo, École polytechnique fédérale de Lausanne
You can see this video (enhanced version) in fullscreen here
Abstract
In recent years, museums, archives and other cultural institutions have initiated important programs to digitize their collections. Millions of artefacts (paintings, engravings, drawings, ancient photographs) are now documented in digital photographic format. Furthermore, through progress in standardization, a growing portion of these images are now available online, in an easily accessible manner through textual metadata. But images are not only text.
How can such large-scale art history collections be made searchable? Can deep learning approaches open new avenues for composing visual queries? What are the new forms of understanding that can be produced if all the images are organized on a large-scale morphological graph? The results of research conducted for the Replica project at the Digital Humanities Lab of École Polytechnique de Lausanne demonstrates that the search for patterns by visual similarity open new discoveries in attribution, production strategies of artistic workshops, circulation of motifs through different geographies, problems of taste evolution and recontextualization of the fortune of certain visual formulas.
Searching for images using other images also allows to approach the problem of iconographic choices in a different way and shows the logic of reciprocal influences between authors independently of stylistic evaluations.
It is becoming clearer that the current extent of our visual knowledge is only the tip of an iceberg of visual document, the largest part being still immersed. Digitization allows many images of artworks that had never even been seen by specialists and curators to come to light and be studied. Simultaneously, as digitization progresses, the images already known get inserted in a progressively more granular network of visual relationships that fosters novel reinterpretations. In this evolution, the logic of the image collections that structured art history for centuries is fading away for the progressive emergence of a single interconnected digital space.
Biography
Isabella di Lenardo holds a Ph.D. in Theories and Art History and is researcher in Digital Humanities and specialist in Digital Urban History. Her research activity is focused on digital tools and methods applied to Urban History. She is an expert in ancient cartography, city representations, cadastral sources interpreted through digital modeling, extraction and analysis systems. She’s also interested in network analysis, questioning the production and circulation of artistic and architectural knowledge in Europe XVIth - XVIIIth centuries in particular on North-South relationships and influences. She leads projects in collaboration with Bibliothèque national de France, Institut National d’Histoire de l’Art, Ecole nationale des chartes, Université Paris I Panthéon-Sorbonne, German Center for the History of Art, Louvre Museum, National Archives of Paris, Historical Library of the City of Paris, and Réunion des musées nationaux. Isabella di Lenardo supervised all the urban modeling simulations for the Venice Time Machine project and acted as content curator for all the exhibitions (Venice Biennale, Grand Palais-Paris, Cité des Sciences-Paris , Datasquare - ArtLab-Lausanne, Museo Correr-Venice).
URI/Permalien:
