Collected Notes 2024 Week
27
- 2024-06-28
- First clustering via pixplot shows some clusters by colors
and strong features such as visible grids or patterns. Not much
visible in terms of details.
- Filtering by year reveals that early games are in the global
center or in the center of clusters. With 1982 comes an
explosion of interfaces that are dispersed all over the
edge-regions, which could be an interesting finding. As in, 1982
starting the time of experimentation. I need to check how this
can be developed further.
- 2024-07-02
- Worked on the outline for Observing
the Coming of Age of Video Game Graphics
- Following Janna Omena’s lead on reflecting our digital
research methods (see Technicity), I
investigated the base approach of pix-plot. It basically uses
Tensorflow’s Inception v3 model for feature extraction and UMAP for the reduction of
dimensionality. Since the project is a bit older I also had a
look out for other projects and found Voxel51’s FiftyOne, which
is like pix-plot on steroids. It allows the application of many
more computer vision models and clustering algorithms, as well
as a better finetuning and filtering of the results.
- A takeaway of my exploration of computer vision models is
the reflection on what features I actually need to extract from
my dataset. I’m certainly not on the side of object
classification and need something that is a tad closer to
low-level feature extraction. This could also be a finding that
I need to discuss with somebody a bit more knowledgeable of
these subjects.
- 2024-07-03
- Worked on the abstract and method parts in Observing
the Coming of Age of Video Game Graphics
- Tried to adjust the pixplot clustering hyperparameters but
that needed another 4 hours.
- Meanwhile I came up with a way of reducing the dataset size
through removing similar images on a per-game basis, which
removed roughly 42% of screenshots. I will try to work with this
reduced dataset in pixplot and fiftyone.
- pixplot with
--min_dist 0
made practically the
same clustering
- 2024-07-04
- 2024-07-05
- Run a larger clustering in fiftyone on 5’000 samples. I used
UMAP and ResNet101 and will look at it later today.
- Added new material to the A
handful of pixels of blood - Extended Abstract
- The clustering is pretty good already and seems to take
shape into a direction with which I can work with. I did some
first explorations and the clusters look interesting. There is
already a trajectory from text to image with mixed interfaces in
between. There are aspects of colors and textures to be
explored. Fiftyone is clearly the better choice to explore the
corpus in that direction. I’m ready to run a clustering on a
larger sample next week. 5’000 is less then 1% of the current
corpus size (73’653 screenshots in total). So I would go for 10%
next week. I might also see if the FiftyOne Similarity
calculation is a better fit then the similar-image-remover
script.