Figure 1: animal toys used for this session. A total of 20.
agenda
workshop process overview
Each group had three animal toys, which the total number of combinations will have will be around 240 variations.
They will map animals to cities.
They have the freedom how to associate a city to the model; some just chose cities they liked and associate animals randomly, some tried to tie it the common characteritic of the model and the city. (like elephant = london’s zoo)
They will disect the animals and decide which part represents which aspects of a city.
Note that for each part, it will represent the same aspect across the thress different animal models they have.
- mix ’n’ match.
group consensus and voting
a tournament like voting session was held to collectively decide which city animal wins.
a simple majority vote. for future sessions. My voting system should be used for this.
results
https://docs.google.com/spreadsheets/d/1By2BweUqJEUEVwto8PQKgUgxE-pnZ3zlKfeBIo0Mz8c/edit?usp=sharing
| rank | head | torso | front leg | end leg |
| 1 | Dragon / Tokyo / skyline | Pteranodon / Jakarta / (mixed) culture | Dragon / Tokyo / tranportation | Brachiosaurus / Kyoto / walkability |
| 2 | Sheep / Awaji-sima / five senses | Winged Lion / Philadelphia / historic value | Winged Lion / Philadelphia / student population | Ankylosaurus / Fujisawa / water front amenities |
| 3 | Aligator / Barcelona / academic facilities | Aligator / Bangkok / Local industry | Aligator / Bangkok / transportation | Cow / Sendai / infrastructure |
Generation
City with the skyline and public transportation of Tokyo, street scape and walkability of Kyoto, and the mixed culture of Jakarta.
ControlNet
bluntly using “canny edge” mode. M-LSD, Normals, segmentation might work?
1st
2nd
3rd
base images
midjourney
the group can take it from here and use different generation methods. simulation, ABM, cities skyline (game), and other image generation methods.