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    Video Quality Assessment Dataset for Smart Public Security Systems

    Thumbnail
    Date
    2020
    Author
    Bezzine I.
    Khan Z.A.
    Beghdadi A.
    Al-Maadeed N.
    Kaaniche M.
    Al-Maadeed, Somaya
    Bouridane A.
    Cheikh F.A.
    ...show more authors ...show less authors
    Metadata
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    Abstract
    Security and monitoring systems are more and more demanding in terms of quality, reliability and flexibility especially those dedicated to video surveillance. The quality of the acquired video signal strongly affects the performance of the high level tasks such as visual tracking, face detection and recognition. The design of a video quality assessment metric dedicated to this particular application requires a preliminary study on the common distortions encountered in video surveillance. To this end, we present in this paper a dataset dedicated to video quality assessment in the context of video surveillance. This database consists of a set of common distortions at different levels of annoyance. The subjective tests are performed using a classical pair comparison protocol with some new configurations. The subjective results obtained through the psycho-visual tests are analyzed and compared to some objective video quality assessment metrics. The preliminary results are encouraging and open a new framework for building smart video surveillance based security systems. Database link: https://data.mendeley.com/datasets/prf8p9rwhd/draft?a=d9646d2f-5154-4d49-8eb3-e7989187a24c
    DOI/handle
    http://dx.doi.org/10.1109/INMIC50486.2020.9318149
    http://hdl.handle.net/10576/31111
    Collections
    • Computer Science & Engineering [‎2428‎ items ]

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