Assessing architectural façade character from line drawings: a computational framework linking formal complexity and order with human perception
Ju Hyun Lee, Michael J. Ostwald, Michael J. DawesPurpose
This study investigates how computationally measured formal properties of building façades relate to human verbal perceptions of façade character. It focuses on two key formal dimensions, complexity and order, and examines whether these measurable visual properties correspond to the language observers use when describing façade drawings.
Design/methodology/approach
The study combined a dataset of 108 façade line drawings with verbal responses collected from 51 participants. Visual complexity was measured using fractal dimension, while formal order was measured using a computational framework based on bilateral symmetry and two-axis rhythm regularity. Participants' spoken descriptions were transcribed and processed to derive two image-level language variables: “complexity-language score” and “order-language score”. Descriptive statistics, Spearman correlation, ordinary least squares regression, and a 2 × 2 complexity-order typology were used to examine the relationships between computational measures and verbalised perceptions.
Findings
The results show that façade drawings vary meaningfully in both computational complexity and formal order. Fractal dimension was positively associated with complexity-related language, while the order index was positively associated with order-related language. Regression models further showed that complexity predicted complexity-language, whereas order predicted order-language. The typology analysis suggested that order-related language was strongest for façades combining relatively low complexity with high order.
Originality/value
The study contributes a reproducible computational framework for analysing façade character from line drawings and linking formal image properties to open verbal descriptions. It also introduces a novel human-centred method for operationalising verbalised perception and connecting computational form analysis with architectural perception research.