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updated/updating programme: http://diversions.lan/pad/p/programme
alex presentation pad http://etherbox.local/pad/p/One_commit_doesn 't_make_a_story

Different orders coexist (Michael Murtaugh + Nicolas Maleve)
"Computational vandalism means working with this and other qualities  of computing; the capacity for repetition, speed, interpretation by  combination, the layering of operations and so on. In this sense,  computational vandalism works with the aesthetic, social, material and  imaginal forces that are gathered as compositional terms within  computing." (Matthew Fuller in an interview with SICV, Vandalist Iconophilia http://editorialconcreta.org/Vandalist-Iconophilia)
As the Scandinavian Institute for Computational Vandalism, Nicolas Malevé and Michael Murtaugh have developed a series of experiments in  connection with the archives of the artists Erkki Kurenniemi, Asger Jorn  and Guttom Guttorsgaard. Probing into large collections of digital and  digitised collections, they employed Computer Vision algorithms as  interlocutors, to explore alternative interpretations, different  orderings and seeing through other eyes. The images started to  masquerade as text, and texts start to behave as images. 
For DiVersions, Michael and Nicolas will turn the SICV toolkit onto  the actual files and databases of the Cinquantenaire museum itself.  Working on the archive as a whole, SICV will redraw relations and  genealogies in the order(s) of art history.


Guttom Guttormsgaard, bought old diary
website, zero metadata, no descriptions

words are everywhere.
huge collector of books, interested in the form & craft

things being brought together in unexpected ways

zooming as the ultimate feature

artist collective who is working at the dairy farm . family, small scale
started from the database dump and the high res photos they had received

basic ways a computer looks at data:
    - data base IDs
 - dimensions
  extremes are interesting

- file size

- time & date of the photographs

datapoint rhythms (lunch!)

The labor that goes into making these images. Work practices are logged too.
Interesting: what does the metadata say about the labour that goes into the images ? 

- reinterpreations of data through algorithm, RGB
white is all green/allred/allbleu

-> filters

updated/updating programme: http://diversions.lan/pad/p/programme
images (thank you Peter, Michael :-)): http://gallery3.constantvzw.org/index.php/DiVersions-Worksession

reference to the red green and blue channels. splitting image into colour channels in the development of the filters
they have to pass a certain treshold, many images are not in
not so many green objects, perceptually not so important as red & blue
entered a series of problems: difference between encoded colour and perceived colou r
Nocilas studied Fine Arts, painting and also worked as a 'house-painter', painting walls :-)
-> has a practice of making colors with pigments.
confronted with a logic that is different, non-human, a 'machine gaze'
they (not N and M) often claim terms that are anthropomorphic, like face detection, but there is a whole stack of techniques that involve the human

- face detection
-hard cascade detection process
trained on frontal faces
'false positives': does it see faces where there is no face? 
'false negatives': does it miss out on faces?

-> relational data, eg chair depicting faces; the algorithm will not make distinction between real face and illustration of face

this collection plays a lot with forms, works well
software developed historically
humans are poor face recognisers. how do we judge the performance of the machine with our own defective apparatus?
see faces where we don't see them, maybe an invitation for us?
An invitation to rethink our understanding of what is a face.

-> create interfaces to see how face recognition works

gradient: first treatment, brightness to darkness, flowing water through that :-)
contours: relates to that, finding edges
sift: selecting interest points, features
t ext recognition 
"the slotmachine interface"


(An invitation to rethink our understanding of what is a face language)

OCR = Optical Character Recognition (when you scan a book, it can detect from the image if there is text, and translate it to machine/human readable text)

there is always text in the material world

each layer comes with specific problems
the algorithms perform better on languages which they have been trained
it looks for texture of text, shapes of letters
text is always material, text doesn't exist in air and the algorithms can help us to pay attention to the space in which text exists

collection of 1400 images
we created random walks, and used them to generate videos
starts with a random image, applies one of the SIFT features, then walks through the 'neighbourhood' of layers: colour, gradients etc. moves through the different orderings of the collection
builds up all layers, picks one & moves to its neighbours
you can get seduced by what it is doing
this provided an exploration of the data set
rediscovering through an algorithmic gaze

we are now busy with publication: applying random walk to pdf

the tyranny of the framework
europeana: overwhelming scale

afternoon workshop: idiosyncratic websites

ex of early netart:
    parallel website: http://www2.tate.org.uk/netart/mongrel/home/default.htm
with collages of paintings & medical imagery
mix in local context of people living around the museum at the time
http://www2.tate.org.uk/netart/mongrel/collections/ (interesting to compare this work to a contemporary "experiment" at tate: http://recognition.tate.org.uk/ )

something for the workshop
i have been working with makefiles
it allows you to work with code and programs
what we propose is, using techniques, create a website, that is based on a common framework
using html, hyperlinks
image maps
putting pdfs or video in
and working with code
in a slightly different way
look at selenium which scrapes sites (and, if wanted interactively)
image editing software like photoshop with greater scripting possibilities
that is what we are proposing
depends on who is here
begin a patchwork, with tools that are something inbetween??

look into images
systematic background sustraction (void)
to also look at the background of the objects
to see how we can do the opposite like background injection or addition to enter into a dialogue with the subject

asger jorn: why do you need objects into a museum as 'mugshots' (why do they need to look like criminals)

alex presentation pad http://etherbox.local/pad/p/One_commit_doesn 't_make_a_story

sorry, it is a labyrinth -- go here: 



James Bridle: Algorithmic Curators?
Ordering  by size, showing the object size.
create catalogues of imaginary exhibitions?
reorganise the storage space by size/weight
Marie: example of library objects sorted by size: Set to human scale.

Tracing the single object to its physical location, through all the different forms of representation.

ORDERING the images in