This study explores the potential of facial emotion recognition as a neurological research tool in urban studies, particularly in privately owned public spaces within highly dense residential areas. Data collected from 30 residents and users was analyzed through capture of facial expressions in real time to three-dimensional design elements. As a result, high recognition rates were achieved for emotions such as “Neutral,” “Happiness,” “Sadness,” and “Frustration.” The study highlights two key findings. Firstly, it underscores the value of facial recognition technology in the spatial cognition of living environments. Secondly, it provides visual mapping of this spatial cognition through Agent-Based Modeling, allowing the nuances of how spatial settings and elements affect users to be captured.
In light of that, this study demonstrates the validity and reliability of facial emotional recognition in urban morphology based on: (a) emotionally-based morphology theories, (b) principles of computer algorithms, and (c) visualization studies.