Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration

Fuente: arXiv
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Autori principali: Meyer, Louie Søs, Aaen, Johanne Engel, Tranberg, Anitamalina Regitse, Kun, Peter, Freiberger, Matthias, Risi, Sebastian, Løvlie, Anders Sundnes
Natura: Preprint
Pubblicazione: 2024
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author Meyer, Louie Søs
Aaen, Johanne Engel
Tranberg, Anitamalina Regitse
Kun, Peter
Freiberger, Matthias
Risi, Sebastian
Løvlie, Anders Sundnes
author_facet Meyer, Louie Søs
Aaen, Johanne Engel
Tranberg, Anitamalina Regitse
Kun, Peter
Freiberger, Matthias
Risi, Sebastian
Løvlie, Anders Sundnes
contents This Research through Design paper explores how object detection may be applied to a large digital art museum collection to facilitate new ways of encountering and experiencing art. We present the design and evaluation of an interactive application called SMKExplore, which allows users to explore a museum's digital collection of paintings by browsing through objects detected in the images, as a novel form of open-ended exploration. We provide three contributions. First, we show how an object detection pipeline can be integrated into a design process for visual exploration. Second, we present the design and development of an app that enables exploration of an art museum's collection. Third, we offer reflections on future possibilities for museums and HCI researchers to incorporate object detection techniques into the digitalization of museums.
format Preprint
id arxiv_https___arxiv_org_abs_2403_19174
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration
Meyer, Louie Søs
Aaen, Johanne Engel
Tranberg, Anitamalina Regitse
Kun, Peter
Freiberger, Matthias
Risi, Sebastian
Løvlie, Anders Sundnes
Human-Computer Interaction
Computer Vision and Pattern Recognition
This Research through Design paper explores how object detection may be applied to a large digital art museum collection to facilitate new ways of encountering and experiencing art. We present the design and evaluation of an interactive application called SMKExplore, which allows users to explore a museum's digital collection of paintings by browsing through objects detected in the images, as a novel form of open-ended exploration. We provide three contributions. First, we show how an object detection pipeline can be integrated into a design process for visual exploration. Second, we present the design and development of an app that enables exploration of an art museum's collection. Third, we offer reflections on future possibilities for museums and HCI researchers to incorporate object detection techniques into the digitalization of museums.
title Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration
topic Human-Computer Interaction
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2403.19174