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Reconstructing Histories: Analyzing Exhibition Photographs with Computational Methods

Heidelberg Collaboratory for Image Processing, IWR, Heidelberg University, 69120 Heidelberg, Germany
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Received: 31 July 2018 / Revised: 24 September 2018 / Accepted: 4 October 2018 / Published: 9 October 2018
(This article belongs to the Special Issue Computational Aesthetics)
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Abstract

Displays of art in public or private spaces have long been of interest to curators, gallerists, artists and art historians. The emergence of gallery paintings at the beginning of the seventeenth century and the photographic documentation of (modern) exhibitions testify to that. Taken as factual documents, these images are not only representative of social status, wealth or the museum’s thematic focus, but also contain information about artistic relations and exhibition practices. Digitization efforts of previous years have made these documents, including photographs, catalogs or press releases, available to public audiences and scholars. While a manual analysis has proved to be insufficient, because of the sheer number of available data, computational approaches and tools allowed for a greater access. The following article describes how digital images of exhibitions, as released by the New York Museum of Modern Art in the fall of 2016, are studied with a retrieval system to analyze in which artistic contexts selected artworks were presented in exhibits. View Full-Text
Keywords: art history; computer vision; digitization; exhibition histories; photographs; visual search; retrieval systems art history; computer vision; digitization; exhibition histories; photographs; visual search; retrieval systems
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Lang, S.; Ommer, B. Reconstructing Histories: Analyzing Exhibition Photographs with Computational Methods. Arts 2018, 7, 64.

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