Normaleyes

'Normaleyes' is an interactive digital artwork exploring how we, as data subjects, are surveilled, captured and analysed, via vectors of difference that function to normalise rather than differentiate us as unique individuals. The project employs real-time face-tracking, calculating the physical location and attitude of each viewer's face as it appears in the camera observing the space in front of the work. Each viewer's captured face image is normalised in size, ratio and point of view (the angle or parallax view of the scene as a whole, determined by the left-right location of the viewer in closest proximity to the display and camera). The resolution of each viewer's face is determined by their distance from the camera and display (the closer to the display the higher the resolution), controlling the size and number of points that comprise the image of the viewer's face. The movement of the viewers, the shifting point of view, dynamic parallax effects and the changing resolution of each layer leads to a moire interplay of the layers generating irridescent hybrid faces that share elements of all the viewer's faces in the scene.

'Normaleyes' integrates aspects of previous interactive artworks, including 'Interferography' (2025), 'Diffusion' (2025) and 'Data Double' (2022), that each explores aspects of visual diffraction of the subject as a form of irridescent data.

Technical specification: Macbook Pro M3 Max, OSX 14.4.1, Processing 4.3 with OpenCV library, Samsung QN800D 8K display, Canon EOS R50 camera with 18-45mm lens. Note that screen recordings are rendered at 4K due to the technical limitations of current screen-recording software on the Mac system. There is four times as much information visible in the live artwork (still images are presented at full 8K resolution - Right-Click on an image to open in a new tab; select the new tab; click on the image when the cursor appears as a magnifying glass, to enlarge it to its original 8K resolution).


Screen recording of 'Normaleyes' being interacted with by two viewers.





CC 2025 Simon Biggs