TY - JOUR
T1 - Floor plan generation
T2 - The interplay among data, machine, and designer
AU - Mostafavi, Fatemeh
AU - van Engelenburg, Casper
AU - Khademi, Seyran
AU - Vrachliotis, Georg
PY - 2024
Y1 - 2024
N2 - Recent advancements in machine learning (ML) in architectural design led to new developments in automated generation of floor plans. However, critical evaluation of ML-based generated floor plans has not progressed proportionally due to the subjectivity and complexity of the assessment, particularly for large and more complex floor plans. Accordingly, a hybrid (quantitative and qualitative) floor plan evaluation scheme is introduced in this study, focusing on multiple architectural aspects. To verify the effectiveness of the proposed framework, the evaluation scheme is applied on the generated floor plans resulting from two baseline computer vision models. The models have been trained on a newly introduced large-scale floor plan dataset called Modified Swiss Dwellings (MSD). The results showed that despite the progression of computer vision models for floor plan generation, they still have difficulty capturing the more complex architectural qualities. In addition, the prospect of floor plan generation and evaluation and possible future developments are discussed.
AB - Recent advancements in machine learning (ML) in architectural design led to new developments in automated generation of floor plans. However, critical evaluation of ML-based generated floor plans has not progressed proportionally due to the subjectivity and complexity of the assessment, particularly for large and more complex floor plans. Accordingly, a hybrid (quantitative and qualitative) floor plan evaluation scheme is introduced in this study, focusing on multiple architectural aspects. To verify the effectiveness of the proposed framework, the evaluation scheme is applied on the generated floor plans resulting from two baseline computer vision models. The models have been trained on a newly introduced large-scale floor plan dataset called Modified Swiss Dwellings (MSD). The results showed that despite the progression of computer vision models for floor plan generation, they still have difficulty capturing the more complex architectural qualities. In addition, the prospect of floor plan generation and evaluation and possible future developments are discussed.
KW - architectural dataset
KW - computer vision
KW - floor plan evaluation
KW - floor plan generation
KW - human-machine interaction
UR - http://www.scopus.com/inward/record.url?scp=85206016696&partnerID=8YFLogxK
U2 - 10.1177/14780771241290649
DO - 10.1177/14780771241290649
M3 - Article
AN - SCOPUS:85206016696
SN - 1478-0771
JO - International Journal of Architectural Computing
JF - International Journal of Architectural Computing
ER -