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dc.contributor.authorGan, Jiangbinen_US
dc.contributor.authorBergen, Philippen_US
dc.contributor.authorThormählen, Thorstenen_US
dc.contributor.authorDrescher, Philipen_US
dc.contributor.authorHagens, Ralfen_US
dc.contributor.editorSchulz, Hans-Jörg and Teschner, Matthias and Wimmer, Michaelen_US
dc.description.abstractIn 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.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.titleNormal Map Bias Reduction for Many-Lights Multi-View Photometric Stereoen_US
dc.description.seriesinformationVision, Modeling and Visualization

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  • VMV19
    ISBN 978-3-03868-098-7

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