This database collects information about games, art and narratives that use or represent machine vision technologies. This is part of the ERC project Machine Vision in Everyday Life: Playful Interactions with Visual Technologies in Digital Art, Games, Narratives and Social Media

Citation: Rettberg, Jill Walker, Linda Kronman, Ragnhild Solberg, Marianne Gunderson, Stein-Magne Bjørklund, Linn Heidi Stokkedal, Kurdin Jacob. 2021. Machine Vision in Art, Games and Narratives. Research database. http://machine-vision.no.

Machine Vision Situations

875 records
Situation Brief description Aesthetic Characteristics
Data-Masks (Series) (reverse engineering facial recognition)

The artist is reverse engineering facial recognition by deconstructing images of faces and then mutating the images until they where again detected by facial detection tools as faces. The artist chose a selection of mutations and made 3D prints of them.

"Data-masks can be understood as visualizations of how machine learning algorithms generalize faces into abstract feature sets"
Source: http://www.sterlingcrispin.com/Sterling_Crispin_Data-masks_MS_Thesis.pdf

Metallic
FACELESS (making a CCTV film)

The artist performs (herself as the character "Ma Nu") in front of security cameras in London and then goes through a bureaucratic process of collecting the films as it is her right according to the UK Data Protection act and EU directives. From the material the artist compiles a film and creates manifesto how to create films using CCTV camera footage. Among other things all other actors need to be anonymised, hence, they remain facesless. "Ma Nu" is also first faceless, but her face gets revealed. 

Glitchy, birds eye view, Pixelated, Low-quality
Gruppebilde Bergen 2020 (assembling a dataset to generate portraits)

The artist is assembling a dataset of citizens living in Bergen. The dataset is used to generate new faces both using the whole dataset or partial datasets classified according to age or neighbourhood (the photographed individuals classify themselves into categories by answering in what part of the city they live and what their age is). The used machine learning system would learn how photographs look like and generate similar ones. Out of several iterations of generated portraits the artist curates images for a group image printed on a big tapestry representing the citizens of Bergen,

Portraits
Sharing locations: YONGSAN & HUMPHREY GARRISON (obfuscating satellite images)

Images in the artwork exposes different tactics mapping platforms (corporations) use to obfuscate and camouflage to hide important infrastructure like military presence at army bases. On the other hand different data layers (e.g. Strava maps) reveal that something is hidden.

Aerial
Sustaining Gazes (measuring the gaze)

When the user interacts with the work the artwork measures where the user gazes. A heat map visualizes were the user looks, however, the patters in the visualization it self attracts and influences the user to gaze where s(he) already has been looking.

Scientific, Abstract