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
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.