AI-Simulated Visual Tracking of Structural Order Perception in Urban Facades: A Case Study from Mashhad, Iran

Aims: In urban design, the structural order of building facades plays a pivotal role in shaping human perception and experience. This study investigates the implicit visual recognition of structural order using subliminal visual tracking analysis. Methodology: Visual Attention Software (VAS) was employed to analyze observers’ visual attention patterns toward diverse façade typologies, including historical and contemporary urban facades in Mashhad, Iran. Findings: Our findings indicate that observers’ subliminal perceptions align with the three-part rules of structural order: contrasting elements on a micro-scale, reduced entropy and connection between micro and macro scales, and a hierarchical connection between levels. Here, we show that observers readily perceive structural similarities on a micro-scale and the totality of forms on a macro-scale, but struggle with perceiving the hierarchical connection between these levels. Conclusion: This study underscores the critical role of multi-scale coherence in façade design across scales and provides insights for enhancing the visual quality and coherence of urban facades.