| id |
caadria2024_331 |
| authors |
Gao, Naixiang |
| year |
2024 |
| title |
Interactive Mediatised Urbanism: Shaping High Emotional Value Food Consumption Spaces With Human Data on Social Media |
| source |
Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 2, pp. 415–424 |
| doi |
https://doi.org/10.52842/conf.caadria.2024.2.415
|
| summary |
Research in the field of shaping urban spaces with emotional values on social media is still lacking. This paper attempts to shape an urban food consumption space with high emotional value through digital interactive media consisting of machine learning and other algorithmic processing of the emotional values contained in images of urban food consumption venues posted by humans on social media for the food consumption process. Images on social media that contain geographic information on the food market with research conditions are used as the data source, which is filtered by algorithms for the emotional value data. The filtered images are put into a machine learning model for training, resulting in a series of spatial images containing high emotional values, which are used as learning objects for the pictures entered by the user community at the input side of the system. The depth information in the output objects is read to transform them into spatial models, and the information from these virtual spatial models that have been learned for higher emotional values is the output of user interactions and the basis for improving the food consumption space. |
| keywords |
social media database, human-urban interactive media, computer visualization, image-to-model, food consumption space, emotional values, machine learning, AR interface |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (1,192,180 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/11/17 22:05 |
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