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    Normal Map Bias Reduction for Many-Lights Multi-View Photometric Stereo

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    Date
    2019
    Author
    Gan, Jiangbin
    Bergen, Philipp
    Thormählen, Thorsten
    Drescher, Philip
    Hagens, Ralf
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    Abstract
    In this paper, we improve upon an existing many-lights multi-view photometric stereo approach. Firstly, we show how to detect continuous regions for normal integration, which leads to a fully automatic reconstruction pipeline. Secondly, we compute perpixel light source visibilities using an initial biased reconstruction in order to update the estimated normal map to a solution with reduced bias. Thirdly, to further improve the normal accuracy, we compensate for interreflections of light between surface locations. Our approach is evaluated on both synthetic and real-world data and it is shown that the normal accuracy is improved by around 50 percent.
    BibTeX
    @inproceedings {10.2312:vmv.20191314,
    booktitle = {Vision, Modeling and Visualization},
    editor = {Schulz, Hans-Jörg and Teschner, Matthias and Wimmer, Michael},
    title = {{Normal Map Bias Reduction for Many-Lights Multi-View Photometric Stereo}},
    author = {Gan, Jiangbin and Bergen, Philipp and Thormählen, Thorsten and Drescher, Philip and Hagens, Ralf},
    year = {2019},
    publisher = {The Eurographics Association},
    ISBN = {978-3-03868-098-7},
    DOI = {10.2312/vmv.20191314}
    }
    URI
    https://doi.org/10.2312/vmv.20191314
    https://diglib.eg.org:443/handle/10.2312/vmv20191314
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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