Towards a framework for collaborative video surveillance system using crowdsourcing

Susumu Saito, Teppei Nakano, Tetsunori Kobayashi

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    This paper proposes a new framework for video surveillance systems for crime prevention. The main purpose of this framework is to help provide reasonable and stable solutions for automated video surveillance systems in a collaborative way. This framework is characterized by a verification process using crowdsourcing after the image analysis process: automated image analyzer detects as many suspicious events as possible followed by filtering process using human intelligence, to achieve both high recall and high precision rates. Here we describe the basic mechanisms for collaboration between camera devices, data stores, image analyzers and surveillance crowds.

    Original languageEnglish
    Title of host publicationProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW
    PublisherAssociation for Computing Machinery
    Pages393-396
    Number of pages4
    Volume26-February-2016
    ISBN (Print)9781450339506
    DOIs
    Publication statusPublished - 2016 Feb 27
    Event19th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2016 - San Francisco, United States
    Duration: 2016 Feb 262016 Mar 2

    Other

    Other19th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2016
    CountryUnited States
    CitySan Francisco
    Period16/2/2616/3/2

    Keywords

    • Collaborative video surveillance
    • Crowdsourcing
    • Framework

    ASJC Scopus subject areas

    • Software
    • Computer Networks and Communications
    • Human-Computer Interaction

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  • Cite this

    Saito, S., Nakano, T., & Kobayashi, T. (2016). Towards a framework for collaborative video surveillance system using crowdsourcing. In Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW (Vol. 26-February-2016, pp. 393-396). Association for Computing Machinery. https://doi.org/10.1145/2818052.2869074