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dc.contributor.authorHe, Zhenbangen_US
dc.contributor.authorWang, Yunhaien_US
dc.contributor.authorCheng, Zhanglinen_US
dc.contributor.editorZhang, Fang-Lue and Eisemann, Elmar and Singh, Karanen_US
dc.description.abstractThe Manhattan-world building is a kind of dominant scene in urban areas. Many existing methods for reconstructing such scenes are either vulnerable to noisy and incomplete data or suffer from high computational complexity. In this paper, we present a novel approach to quickly reconstruct lightweight Manhattan-world urban building models from images. Our key idea is to reconstruct buildings through the salient feature - corners. Given a set of urban building images, Structure-from- Motion and 3D line reconstruction operations are applied first to recover camera poses, sparse point clouds, and line clouds. Then we use orthogonal planes detected from the line cloud to generate corners, which indicate a part of possible buildings. Starting from the corners, we fit cubes to point clouds by optimizing corner parameters and obtain cube representations of corresponding buildings. Finally, a registration step is performed on cube representations to generate more accurate models. Experiment results show that our approach can handle some nasty cases containing noisy and incomplete data, meanwhile, output lightweight polygonal building models with a low time-consuming.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectShape modeling
dc.titleManhattan-world Urban Building Reconstruction by Fitting Cubesen_US
dc.description.seriesinformationComputer Graphics Forum

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  • 40-Issue 7
    Pacific Graphics 2021 - Symposium Proceedings

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