TY - GEN
T1 - Approach to auto-recognition of design elements for the intelligent management of interior pictures
AU - Kim, Jinsung
AU - Song, Jaeyeol
AU - Lee, Jin Kook
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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)
AB - 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)
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M3 - Conference contribution
T3 - Intelligent and Informed - Proceedings of the 24th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2019
SP - 785
EP - 794
BT - Intelligent and Informed - Proceedings of the 24th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2019
A2 - Haeusler, Matthias Hank
A2 - Schnabel, Marc Aurel
A2 - Fukuda, Tomohiro
PB - The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA)
T2 - 24th International Conference on Computer-Aided Architectural Design Research in Asia: Intelligent and Informed, CAADRIA 2019
Y2 - 15 April 2019 through 18 April 2019
ER -