Zhao Jinjing, Chen Yunfan, Li Yancheng, Xu Haotian, Xu Jingjing, Li Xuliang, Zhang Hong, Jin Lei, Xu Shengyong
School of Electronics, Peking University, Beijing 100871, China.
School of Integrated Circuits, Shandong University, Jinan 250100, China.
Sensors (Basel). 2025 Feb 24;25(5):1375. doi: 10.3390/s25051375.
As urban environments become increasingly interconnected, the demand for precise and efficient pedestrian solutions in digitalized smart cities has grown significantly. This study introduces a scalable spatial visualization system designed to enhance interactions between individuals and the street in outdoor sidewalk environments. The system operates in two main phases: the spatial prior phase and the target localization phase. In the spatial prior phase, the system captures the user's perspective using first-person visual data and leverages landmark elements within the sidewalk environment to localize the user's camera. In the target localization phase, the system detects surrounding objects, such as pedestrians or cyclists, using high-angle closed-circuit television (CCTV) cameras. The system was deployed in a real-world sidewalk environment at an intersection on a university campus. By combining user location data with CCTV observations, a 4D+ virtual monitoring system was developed to present a spatiotemporal visualization of the mobile participants within the user's surrounding sidewalk space. Experimental results show that the landmark-based localization method achieves a planar positioning error of 0.468 m and a height error of 0.120 m on average. With the assistance of CCTV cameras, the localization of other targets maintains an overall error of 0.24 m. This system establishes the spatial relationship between pedestrians and the street by integrating detailed sidewalk views, with promising applications for pedestrian navigation and the potential to enhance pedestrian-friendly urban ecosystems.
随着城市环境的互联程度日益提高,数字化智慧城市中对精确高效的行人解决方案的需求显著增长。本研究介绍了一种可扩展的空间可视化系统,旨在增强户外人行道环境中个人与街道之间的互动。该系统分两个主要阶段运行:空间先验阶段和目标定位阶段。在空间先验阶段,系统使用第一人称视觉数据捕捉用户视角,并利用人行道环境中的地标元素来定位用户的摄像头。在目标定位阶段,系统使用高角度闭路电视(CCTV)摄像头检测周围的物体,如行人或骑自行车的人。该系统部署在大学校园一个十字路口的真实人行道环境中。通过将用户位置数据与CCTV观测结果相结合,开发了一个4D+虚拟监控系统,以呈现用户周围人行道空间内移动参与者的时空可视化。实验结果表明,基于地标的定位方法平均实现平面定位误差0.468米,高度误差0.120米。在CCTV摄像头的辅助下,其他目标的定位总体误差保持在0.24米。该系统通过整合详细的人行道视图建立了行人和街道之间的空间关系,在行人导航方面有广阔的应用前景,并有可能增强行人友好型城市生态系统。