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    Mobile Image Retargeting

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    049-056.pdf (2.456Mb)
    mir_benchmark_code_videos.zip (126.9Mb)
    Date
    2013
    Author
    Graf, Daniel
    Panozzo, Daniele
    Sorkine-Hornung, Olga
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    Abstract
    We propose an algorithm for axis-aligned content-aware image retargeting that is specifically optimized for mobile devices, and we show that interactive image retargeting is possible even with a low-power, mobile CPU. Our retargeting operator is based on non-uniform scaling and cropping and produces results that are on par with state-of-the-art on a large collection of images. Taking the limited screen space of mobile devices into account, we design a novel user interface that allows painting the saliency map directly onto the retargeted image while the system is continuously recomputing the retargeted result at interactive rates. Finally, we apply our algorithm in a picture gallery application to greatly improve the screen space utilization in mobile device settings.
    BibTeX
    @inproceedings {10.2312:PE.VMV.VMV13.049-056,
    booktitle = {Vision, Modeling & Visualization},
    editor = {Michael Bronstein and Jean Favre and Kai Hormann},
    title = {{Mobile Image Retargeting}},
    author = {Graf, Daniel and Panozzo, Daniele and Sorkine-Hornung, Olga},
    year = {2013},
    publisher = {The Eurographics Association},
    ISBN = {978-3-905674-51-4},
    DOI = {10.2312/PE.VMV.VMV13.049-056}
    }
    URI
    http://dx.doi.org/10.2312/PE.VMV.VMV13.049-056
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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