| id |
caadria2019_109 |
| authors |
Kim, Jinsung, Song, Jaeyeol and Lee, Jin-Kook |
| year |
2019 |
| title |
Approach to Auto-recognition of Design Elements for the Intelligent Management of Interior Pictures |
| doi |
https://doi.org/10.52842/conf.caadria.2019.2.785
|
| source |
M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 785-794 |
| summary |
This paper explores automated recognition of elements in interior design pictures for an intelligent design reference management system. Precedent design references have a significant role to help architects, designer and even clients in general architecture design process. Pictures are one of the representation that could exactly show a kind of design idea and knowledge. Due to the velocity, variety and volume of reference pictures data with growth of references platform, it is hard and time-consuming to handle the data with current manual way. To solve this problem , this paper depicts a deep learning-based approach to figuring out design elements and recognizing the design feature of them on the interior pictures using faster-RCNN and CNN algorithms. The targets are the residential furniture such as a table and a seating. Through proposed application, input pictures can automatically have tagging data as follows; seating1(type: sofa, seating capacity: two-seaters, design style: classic) |
| keywords |
Interior design picture; Design element; Design feature; Automated recognition; Design Reference management |
| series |
CAADRIA |
| email |
leejinkook@yonsei.ac.kr |
| full text |
 file.pdf (2,707,585 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/06/07 07:52 |
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