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    • 38-Issue 7
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    Reliable Rolling-guided Point Normal Filtering for Surface Texture Removal

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    Date
    2019
    Author
    Sun, Yangxing ORCID
    Chen, Honghua
    Qin, Jing
    Li, Hongwei
    Wei, Mingqiang
    Zong, Hua
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    Abstract
    Semantic surface decomposition (SSD) facilitates various geometry processing and product re-design tasks. Filter-based techniques are meaningful and widely used to achieve the SSD, which however often leads to surface either under-fitting or overfitting. In this paper, we propose a reliable rolling-guided point normal filtering method to decompose textures from a captured point cloud surface. Our method is built on the geometry assumption that 3D surfaces are comprised of an underlying shape (US) and a variety of bump ups and downs (BUDs) on the US. We have three core contributions. First, by considering the BUDs as surface textures, we present a RANSAC-based sub-neighborhood detection scheme to distinguish the US and the textures. Second, to better preserve the US (especially the prominent structures), we introduce a patch shift scheme to estimate the guidance normal for feeding the rolling-guided filter. Third, we formulate a new position updating scheme to alleviate the common uneven distribution of points. Both visual and numerical experiments demonstrate that our method is comparable to state-of-the-art methods in terms of the robustness of texture removal and the effectiveness of the underlying shape preservation.
    BibTeX
    @article {10.1111:cgf.13874,
    journal = {Computer Graphics Forum},
    title = {{Reliable Rolling-guided Point Normal Filtering for Surface Texture Removal}},
    author = {Sun, Yangxing and Chen, Honghua and Qin, Jing and Li, Hongwei and Wei, Mingqiang and Zong, Hua},
    year = {2019},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.13874}
    }
    URI
    https://doi.org/10.1111/cgf.13874
    https://diglib.eg.org:443/handle/10.1111/cgf13874
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    System hosted at  Graz University of Technology.
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