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International Conference on Web Information Systems Engineering

WISE 2017: Web Information Systems Engineering – WISE 2017 pp 3–18Cite as

Real-Time Target Tracking Through Mobile Crowdsensing

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10570))

Abstract

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.

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Acknowledgement

This work is supported by Chinese National Research Fund (NSFC) Key Project No.61532013; National China 973 Project No.2015CB352401; Shanghai Scientific Innovation Act of STCSM No.15JC1402400 and 985 Project of Shanghai Jiao Tong University with No.WF220103001.

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Authors and Affiliations

  1. Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China

    Jinyu Shi & Weijia Jia

Authors
  1. Jinyu Shi
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  2. Weijia Jia
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Corresponding author

Correspondence to Weijia Jia .

Editor information

Editors and Affiliations

  1. University of Sydney, Darlington, NSW, Australia

    Athman Bouguettaya

  2. Zhejiang University, Hangzhou, China

    Yunjun Gao

  3. Institute of Computing for Physics and Technology, Protvino, Russia

    Andrey Klimenko

  4. Nanyang Technological University, Singapore, Singapore

    Lu Chen

  5. King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

    Xiangliang Zhang

  6. Institute of Computing for Physics and Technology, Protvino, Russia

    Fedor Dzerzhinskiy

  7. Shanghai Jiao Tong University, Minhang Qu, China

    Weijia Jia

  8. Institute of Computing for Physics and Technology, Protvino, Russia

    Stanislav V. Klimenko

  9. City University of Hong Kong, Kowloon, Hong Kong

    Qing Li

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Shi, J., Jia, W. (2017). Real-Time Target Tracking Through Mobile Crowdsensing. In: Bouguettaya, A., et al. Web Information Systems Engineering – WISE 2017. WISE 2017. Lecture Notes in Computer Science(), vol 10570. Springer, Cham. https://doi.org/10.1007/978-3-319-68786-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-68786-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68785-8

  • Online ISBN: 978-3-319-68786-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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