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    • 38-Issue 7
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    • Volume 38 (2019)
    • 38-Issue 7
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    Imitating Popular Photos to Select Views for an Indoor Scene

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    user_study_results.pdf (1.063Mb)
    Date
    2019
    Author
    Su, Rung-De
    Liao, Zhe-Yo
    Chen, Li-Chi
    Tung, Ai-Ling
    Wang, Yu-Shuen
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    Abstract
    Selecting informative and visually appealing views for 3D indoor scenes is beneficial for the housing, decoration, and entertainment industries. A set of views that exhibit comfort, aesthetics, and functionality of a particular scene can attract customers and facilitate business transactions. However, selecting views for an indoor scene is challenging because the system has to consider not only the need to reveal as much information as possible, but also object arrangements, occlusions, and characteristics. Since there can be many principles utilized to guide the view selection, and various principles to follow under different circumstances, we achieve the goal by imitating popular photos on the Internet. Specifically, we select the view that can optimize the contour similarity of corresponding objects to the photo. Because the selected view can be inadequate if object arrangements in the 3D scene and the photo are different, our system imitates many popular photos and selects a certain number of views. After that, it clusters the selected views and determines the view/cluster centers by the weighted average to finally exhibit the scene. Experimental results demonstrate that the views selected by our method are visually appealing.
    BibTeX
    @article {10.1111:cgf.13823,
    journal = {Computer Graphics Forum},
    title = {{Imitating Popular Photos to Select Views for an Indoor Scene}},
    author = {Su, Rung-De and Liao, Zhe-Yo and Chen, Li-Chi and Tung, Ai-Ling and Wang, Yu-Shuen},
    year = {2019},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.13823}
    }
    URI
    https://doi.org/10.1111/cgf.13823
    https://diglib.eg.org:443/handle/10.1111/cgf13823
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    Eurographics Association copyright © 2013 - 2022 
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    Theme by @mire NV
    System hosted at  Graz University of Technology.
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