A general framework for managing and processing live video data with privacy protection

    Authors

    A. J. Aved;K. A. Hua

    Comments

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    Abbreviated Journal Title

    Multimedia Syst.

    Keywords

    Query language; Privacy framework; Video database system; Real-time; Object recognition; Object tracking; DATABASES; SYSTEM; Computer Science, Information Systems; Computer Science, Theory &; Methods

    Abstract

    Though a large body of existing work on video surveillance focuses on image and video processing techniques, few address the usability of such systems, and in particular privacy issues. This study fuses concepts from stream processing and content-based image retrieval to construct a privacy-preserving framework for rapid development and deployment of video surveillance applications. Privacy policies, instantiated to as privacy filters, may be applied both granularly and hierarchically. Privacy filters are granular as they are applicable to specific objects appearing in the video streams. They are hierarchal because they can be specified at specific objects in the framework (e.g., users, cameras) and are combined such that the disseminated video stream adheres to the most stringent aspect specified in the cascade of all privacy filters relevant to a video stream or query. To support this privacy framework, we extend our Live Video Database Model with an informatics-based approach to object recognition and tracking and add an intrinsic privacy model that provides a level of privacy protection not previously available for real-time streaming video data. The proposed framework also provides a formal approach to implement and enforce privacy policies that are verifiable, an important step towards privacy certification of video surveillance systems through a standardized privacy specification language.

    Journal Title

    Multimedia Systems

    Volume

    18

    Issue/Number

    2

    Publication Date

    1-1-2012

    Document Type

    Article

    Language

    English

    First Page

    123

    Last Page

    143

    WOS Identifier

    WOS:000300669000003

    ISSN

    0942-4962

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