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    • 37-Issue 8
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    FTP-SC: Fuzzy Topology Preserving Stroke Correspondence

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    Date
    2018
    Author
    Yang, Wenwu
    Seah, Hock-Soon
    Chen, Quan
    Liew, Hong-Ze
    Sýkora, Daniel ORCID
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    Abstract
    Stroke correspondence construction is a precondition for vectorized 2D animation inbetweening and remains a challenging problem. This paper introduces the FTP-SC, a fuzzy topology preserving stroke correspondence technique, which is accurate and provides the user more effective control on the correspondence result than previous matching approaches. The method employs a two-stage scheme to progressively establish the stroke correspondence construction between the keyframes. In the first stage, the stroke correspondences with high confidence are constructed by enforcing the preservation of the so-called “fuzzy topology” which encodes intrinsic connectivity among the neighboring strokes. Starting with the high-confidence correspondences, the second stage performs a greedy matching algorithm to generate a full correspondence between the strokes. Experimental results show that the FTP-SC outperforms the existing approaches and can establish the stroke correspondence with a reasonable amount of user interaction even for keyframes with large geometric and spatial variations between strokes.
    BibTeX
    @article {10.1111:cgf.13518,
    journal = {Computer Graphics Forum},
    title = {{FTP-SC: Fuzzy Topology Preserving Stroke Correspondence}},
    author = {Yang, Wenwu and Seah, Hock-Soon and Chen, Quan and Liew, Hong-Ze and Sýkora, Daniel},
    year = {2018},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.13518}
    }
    URI
    https://doi.org/10.1111/cgf.13518
    https://diglib.eg.org:443/handle/10.1111/cgf13518
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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