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

要旨

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.

著者
Louie Søs. Meyer
IT University of Copenhagen, Copenhagen, Denmark
Johanne Engel Aaen
IT University of Copenhagen, Copenhagen, Denmark
Anitamalina Regitse Tranberg
IT University of Copenhagen, Copenhagen, Denmark
Peter Kun
IT University of Copenhagen, Copenhagen, Denmark
Matthias Freiberger
IT University of Copenhagen, Copenhagen, Denmark
Sebastian Risi
IT University of Copenhagen, Copenhagen, Denmark
Anders Sundnes. Løvlie
IT University of Copenhagen, Copenhagen, Denmark
論文URL

https://doi.org/10.1145/3613904.3642157

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Remote Presentations: Highlight on Creative HCI

Remote Sessions
11 件の発表
2024-05-15 18:00:00
2024-05-16 02:20:00