Machine Vision

Machine Vision trademark blue

Machine Vision in Everyday Life: Playful Interactions with Visual Technologies in Digital Art, Games, Narratives and Social Media is a five year, ERC-funded project that explores how new algorithmic images are affecting us as a society and as individuals. Professor Jill Walker Rettberg is the principal investigator of Machine Vision, which runs from 2018-2023. A five page project summary is available.

Blurry blue image showing a crowd of people with green boxes superimposed on the image, suggesting some kind of machine vision.

The Machine Vision project receives funding for a LARP and an exhibition

The ERC project MACHINE VISION has received funding from the Norwegian Research Council to develop a live action role-playing game and an exhibition at the University Museum.

Introducing our database
Jill introducing Machine Vision to the group

Presented the Machine Vision database for the first time

Jill, Ragnhild and Linn Heidi introduced the database for the first time at Nordmedia in Malmø.

Screenshot of front page of database showing description and a list of works.

Machine Vision in Art, Games and Narratives

The Machine Vision Database collects information about games, art and narratives that use or represent machine vision technologies. By the summer of 2020 it will be fully developed, and the project will use network analysis and other methods to explore and analyse the data.

Photo of a wall with names written on it. In the shiny surface of the wall you can see the reflection of people sitting at tables, and a view of buildings seen out of large windows.

Future Histories of Machine Vision

Scholars, artists and designers met for a two-day workshop to continue work on an anthology to be titled "Future Histories of Machine Vision".

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Follow the Machine Vision project in Social Media

Machine Vision is growing and has a new Tumblr with weekly updates.

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771800).