Compact video fingerprinting via structural graphical models

    Research output: Contribution to journalArticlepeer-review

    18 Scopus citations

    Abstract

    Much previous work in video fingerprinting has focused on robustness and security issues, but the compactness requirement, i.e., the hash should be of a short length with acceptable robustness and discriminability, continues to be a significant practical challenge. In this paper, we propose a video fingerprinting method with explicit attention on compactness. First, we develop a new graphical representation of the video which reduces temporal redundancies and makes robust feature extraction much more economical. Second, a randomized adaptive quantizer is proposed to further decrease the final hash length while maintaining acceptable detection performance in terms of receiver operating characteristics (ROCs). Experimental results reveal that the proposed method offers a more favorable robustness versus discriminability tradeoff over the state of the art particularly when the bit budget of the video fingerprint is low.

    Original languageEnglish (US)
    Article number6578150
    Pages (from-to)1709-1721
    Number of pages13
    JournalIEEE Transactions on Information Forensics and Security
    Volume8
    Issue number11
    DOIs
    StatePublished - Oct 7 2013

    All Science Journal Classification (ASJC) codes

    • Safety, Risk, Reliability and Quality
    • Computer Networks and Communications

    Fingerprint Dive into the research topics of 'Compact video fingerprinting via structural graphical models'. Together they form a unique fingerprint.

    Cite this