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

Louie Søs Meyer, Johanne Engel Aaen, Anitamalina Regitse Tranberg, Peter Kun, Matthias Freiberger, Sebastian Risi, Anders Sundnes Løvlie

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

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.
Original languageEnglish
Title of host publicationAlgorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration
Number of pages18
Publication date11 May 2024
Pages1-18
DOIs
Publication statusPublished - 11 May 2024
SeriesACM Annual Conference on Human Factors in Computing Systems (CHI)

Keywords

  • Object Detection
  • Art
  • Experience Design
  • Exploratory Search
  • Computer Vision

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