Multidimensional Street View Representation and Association Analysis for Exploring Human Subjective Perception Differences in East Asian and European Cities

Urban landscapes exhibit significant regional differences shaped by geography, history, and culture, yet how these variations influence human perception remains underexplored. This study investigates the impact of street scene characteristics on human perceptions in East Asian and European cities by analyzing the large-scale MIT Place Pulse 2.0 dataset. We employ DeepLab v3+ and Mask R-CNN to extract multidimensional physical and visual features and utilize logistic regression to model their association with six subjective perceptions. The findings reveal significant cultural differences: streets in East Asian cities are characterized by higher compactness and brightness, whereas European city streets exhibit greater levels of greening and openness. While perceptions of aesthetics and liveliness show cross-cultural consistency, the mechanisms influencing safety and wealth perceptions diverge significantly; for instance, East Asian cities associate safety with road openness, while European cities favor greater enclosure. The study provides practical insights for creating urban environments that resonate with local cultural identities, enhancing well-being and supporting sustainable urban development.