Pedestrian Origin-Destination Estimation Based on Multi-Camera Person Re-Identification
文献类型：期刊论文
| 作者 | Li, Yan3,4; Sarvi, Majid4; Khoshelham, Kourosh4; Zhang, Yuyang1,2; Jiang, Yazhen3 |
| 刊名 | SENSORS
 |
| 出版日期 | 2022-10-01 |
| 卷号 | 22期号:19页码:13 |
| 关键词 | pedestrian origin-destination estimation multi-view video surveillance pedestrian trajectories person re-identification |
| DOI | 10.3390/s22197429 |
| 通讯作者 | Zhang, Yuyang(yuyond@ncut.edu.cn) ; Jiang, Yazhen(jiangyz@lreis.ac.cn) |
| 英文摘要 | Pedestrian origin-destination (O-D) estimates that record traffic flows between origins and destinations, are essential for the management of pedestrian facilities including pedestrian flow simulation in the planning phase and crowd control in the operation phase. However, current O-D data collection techniques such as surveys, mobile sensing using GPS, Wi-Fi, and Bluetooth, and smart card data have the disadvantage that they are either time consuming and costly, or cannot provide complete O-D information for pedestrian facilities without entrances and exits or pedestrian flow inside the facilities. Due to the full coverage of CCTV cameras and the huge potential of image processing techniques, we address the challenges of pedestrian O-D estimation and propose an image-based O-D estimation framework. By identifying the same person in disjoint camera views, the O-D trajectory of each identity can be accurately generated. Then, state-of-the-art deep neural networks (DNNs) for person re-ID at different congestion levels were compared and improved. Finally, an O-D matrix based on trajectories was generated and the resident time was calculated, which provides recommendations for pedestrian facility improvement. The factors that affect the accuracy of the framework are discussed in this paper, which we believe could provide new insights and stimulate further research into the application of the Internet of cameras to intelligent transport infrastructure management. |
| WOS关键词 | BEHAVIOR ; NETWORK ; SYSTEM |
| 资助项目 | State Key Laboratory of Resources and Environmental Information System |
| WOS研究方向 | Chemistry ; Engineering ; Instruments & Instrumentation |
| 语种 | 英语 |
| WOS记录号 | WOS:000867181300001 |
| 出版者 | MDPI |
| 资助机构 | State Key Laboratory of Resources and Environmental Information System |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/185785]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Yuyang; Jiang, Yazhen |
| 作者单位 | 1.Tsinghua Univ, Dept Urban Planning, Beijing 100084, Peoples R China 2.North China Univ Technol, Dept Urban Planning & Landscape, Beijing 100144, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.Univ Melbourne, Dept Infrastruct Engn, Melbourne, Vic 3010, Australia |
| 推荐引用方式 GB/T 7714 | Li, Yan,Sarvi, Majid,Khoshelham, Kourosh,et al. Pedestrian Origin-Destination Estimation Based on Multi-Camera Person Re-Identification[J]. SENSORS,2022,22(19):13. |
| APA | Li, Yan,Sarvi, Majid,Khoshelham, Kourosh,Zhang, Yuyang,&Jiang, Yazhen.(2022).Pedestrian Origin-Destination Estimation Based on Multi-Camera Person Re-Identification.SENSORS,22(19),13. |
| MLA | Li, Yan,et al."Pedestrian Origin-Destination Estimation Based on Multi-Camera Person Re-Identification".SENSORS 22.19(2022):13. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。