科研成果详情

题名Real-time target tracking through mobile crowdsensing
作者
发表日期2017
会议名称18th International Conference on Web Information Systems Engineering, WISE 2017
会议录名称Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN978-3-319-68786-5
ISSN0302-9743
卷号10570
页码3-18
会议日期October 7-11, 2017
会议地点Puschino, Russia
出版者Springer Verlag
摘要

In order to track a single target in real-time across a large area, we proposed a novel method which combines mobile crowdsensing and existing sparse camera networks. Tracking is proceeded by reports, which either come from cameras or smart phone users. Intra-camera tracking is performed on selected cameras to identify target, and smart phone users can report with live photo or text when seeing the target. Such schema can largely help tracking target within blind area and increase the accuracy of target identification, due to the better identification ability of human eyes. Novel validation and correction mechanisms are designed to eliminate false reports, which ensures the robustness of our method. Compared with traditional cross-camera tracking methods, our design can be performed in real-time with better performance even if the target has appearance changes during the tracking. Simulations are done using road structures of our university, which validate the accuracy and robustness of our design. © 2017, Springer International Publishing AG.

关键词Crowdsensing Real-time Target tracking
DOI10.1007/978-3-319-68786-5_1
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收录类别CPCI-S
语种英语English
WOS研究方向Computer Science
WOS类目Computer Science ; Artificial Intelligence Computer Science, Information SystemsComputer Science ; Software Engineering Computer Science ; Theory & Methods
WOS记录号WOS:000739732200001
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/4502
专题个人在本单位外知识产出
作者单位
Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China
推荐引用方式
GB/T 7714
Shi, Jinyu,Jia, Weijia. Real-time target tracking through mobile crowdsensing[C]: Springer Verlag, 2017: 3-18.
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