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Pedestrian Origin-Destination Estimation Based on Multi-Camera Person Re-Identification

文献类型：期刊论文

作者Li, Yan1,2; Sarvi, Majid2; Khoshelham, Kourosh2; Zhang, Yuyang3,4; Jiang, Yazhen1
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
DOI10.3390/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.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
2.Univ Melbourne, Dept Infrastruct Engn, Melbourne, Vic 3010, Australia
3.North China Univ Technol, Dept Urban Planning & Landscape, Beijing 100144, Peoples R China
4.Tsinghua Univ, Dept Urban Planning, Beijing 100084, Peoples R China
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

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