公共空间
空格(标点符号)
计算机视觉
计算机科学
互联网隐私
验光服务
心理学
计算机图形学(图像)
人机交互
人工智能
工程类
建筑工程
医学
操作系统
作者
K. L. He,Haoxuan Li,Huanjia Zhang,Qin Hu,Young J. Yu,Waishan Qiu
标识
DOI:10.1177/23998083251328771
摘要
Understanding pedestrian behavior is crucial to inform public space design. However, being laborious, Gehl’s Public Space and Public Life (PSPL) framework is restricted to a small scale. Although prior studies have utilized computer vision (CV), they either focused on monitoring social distancing or measuring urban vitality, ignoring the subtle interplay between public space and public life. This study utilizes webcam data to track walk and stay behaviors, investigating their associations with public space features including point of interest, façade quality, and street furniture. Our findings extend PSPL principles. First, pedestrians tend to stand in less private places with good visual connectivity, indicating that privacy matters less to standing than sitting. Second, pedestrians walk along the edge in large-scale spaces while keeping in the middle in small spaces. Third, although all POIs affect vitality, certain types are more effective (i.e., catering). Fourth, a good place to stay must be convenient to walk through. Our CV framework partially automates PSPL without incurring labor costs. Urban design studies can use the operationalized CV pipeline to draw evidence-based design recommendations and monitor people-space interactions at large scale.
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