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    Key-frame Based Spatiotemporal Scribble Propagation

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    Date
    2015
    Author
    Dogan, Pelin
    Aydın, Tunç Ozan
    Stefanoski, Nikolce
    Smolic, Aljoscha
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    Abstract
    We present a practical, key-frame based scribble propagation framework. Our method builds upon recent advances in spatiotemporal filtering by adding key-components required for achieving seamless temporal propagation. To that end, we propose a temporal propagation scheme for eliminating holes in regions where no motion path reaches reliably. Additionally, to facilitate the practical use of our technique we formulate a pair of image edge metrics influenced from the body of work on edge-aware filtering, and introduce the ""hybrid scribble propagation"" concept where each scribble's propagation can be controlled by user defined edge stopping criteria. Our method improves the current state-of-the-art in the quality of propagation results and in terms of memory complexity. Importantly, our method operates on a limited, user defined temporal window and therefore has a constant memory complexity (instead of linear) and thus scales to arbitrary length videos. The quality of our propagation results is demonstrated for various video processing applications such as mixed HDR video tone mapping, artificial depth of field for video and local video recoloring.
    BibTeX
    @inproceedings {10.2312:wiced.20151073,
    booktitle = {Eurographics Workshop on Intelligent Cinematography and Editing},
    editor = {W. Bares and M. Christie and R. Ronfard},
    title = {{Key-frame Based Spatiotemporal Scribble Propagation}},
    author = {Dogan, Pelin and Aydın, Tunç Ozan and Stefanoski, Nikolce and Smolic, Aljoscha},
    year = {2015},
    publisher = {The Eurographics Association},
    ISSN = {2411-9733},
    ISBN = {978-3-905674-79-8},
    DOI = {10.2312/wiced.20151073}
    }
    URI
    http://dx.doi.org/10.2312/wiced.20151073
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA