| id |
caadria2016_445 |
| authors |
Silvestre, Joaquim; Franc?ois Gue?na and Yasushi Ikeda |
| year |
2016 |
| title |
Edition-Oriented 3D Model Rebuilt from Photography |
| doi |
https://doi.org/10.52842/conf.caadria.2016.445
|
| source |
Living Systems and Micro-Utopias: Towards Continuous Designing, Proceedings of the 21st International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2016) / Melbourne 30 March–2 April 2016, pp. 445-454 |
| summary |
The topic of this paper is about a technique to turn pictures into an intuitively modifiable 3D model. The research employs an analytical method using algorithms to conceptualise and digital- ise architectural spaces in order to highlight parametric shapes. Usual- ly, from one group of digital photos, photogrammetry techniques pro- duce a 3D-model mesh through a high-density 3D point cloud. This discordance between our intuitive partitioning of the mesh and its bare polygonal structure makes it interact poorly compared to the af- fordance of shape and component in our daily experience. Through a capture device, a visualisation of architecture in a digital data form is produced. They are processed by computer vision algorithms and ma- chine learning systems in order to be refined into a parametric model. Parametric elements can be described as a compound of formulas and parameters. By keeping the formula and changing the parameters, the- se elements can be easily modified in a range of likenesses. After be- ing detected during scans, these shapes can be adapted to fit the inten- tion of the designer during the design phase. |
| keywords |
Photogrammetry; convolutional neural network; 3D model; design tool |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (25,234,811 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/06/07 07:56 |
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