| Title |
A Study on the Method for Visual Perception of Architectural Form through Artificial Intelligence |
| Authors |
Seo Dong-Yeon ; Lee Kyuong-Hoi |
| Keywords |
Visual Perception ; Digital Image Processing ; Architectural Form ; CAAD ; |
| Abstract |
Perceiving a shape is to capture prominent elements of an object. To humans, a few selected signs are not only sufficient for identification but also determine the impression of the objects. In this respect, CAAD system should recognize architectural form in the same way of human to support aesthetic ability of designers and users.
Through the analysis of visual perception, vision was separated to low-level vision and high-level vision. Edge detection and neural network were selected to model after low-level vision and high-level vision. The 24 images of building, tree and landscape were processed by edge detection and trained by neural network. And 24 new images were used to test trained network. The test shows that trained network gives right perception result toward each images with low error rate.
This study is on the meaning of artificial intelligence in design process rather than on the design automation strategy through artificial intelligence. |