Bibliographic Details
Title: |
4D+ City Sidewalk: Integrating Pedestrian View into Sidewalk Spaces to Support User-Centric Urban Spatial Perception. |
Authors: |
Zhao, Jinjing1 (AUTHOR), Chen, Yunfan1,2 (AUTHOR), Li, Yancheng1,3 (AUTHOR), Xu, Haotian1,4 (AUTHOR) xhtxys@pku.edu.cn, Xu, Jingjing1,2 (AUTHOR), Li, Xuliang2,3 (AUTHOR), Zhang, Hong3 (AUTHOR) jinlei@alpheus.com.cn, Jin, Lei4 (AUTHOR), Xu, Shengyong1 (AUTHOR) |
Source: |
Sensors (14248220). Mar2025, Vol. 25 Issue 5, p1375. 19p. |
Subject Terms: |
*LOCATION data, *SPACE perception, *URBAN ecology, *SMART cities, *CLOSED-circuit television |
Abstract: |
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. [ABSTRACT FROM AUTHOR] |
|
Copyright of Sensors (14248220) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
Database: |
Academic Search Complete |
Full text is not displayed to guests. |
Login for full access.
|