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• W2892904655 abstract "We address the problem of mesh reconstruction from live RGB-D video, assuming a calibrated camera and poses provided externally (e.g., by a SLAM system). In contrast to most existing approaches, we do not fuse depth measurements in a volume but in a dense surfel cloud. We asynchronously (re)triangulate the smoothed surfels to reconstruct a surface mesh. This novel approach enables to maintain a dense surface representation of the scene during SLAM which can quickly adapt to loop closures. This is possible by deforming the surfel cloud and asynchronously remeshing the surface where necessary. The surfel-based representation also naturally supports strongly varying scan resolution. In particular, it reconstructs colors at the input camera's resolution. Moreover, in contrast to many volumetric approaches, ours can reconstruct thin objects since objects do not need to enclose a volume. We demonstrate our approach in a number of experiments, showing that it produces reconstructions that are competitive with the state-of-the-art, and we discuss its advantages and limitations. The algorithm (excluding loop closure functionality) is available as open source at https://github.com/puzzlepaint/surfelmeshing." @default.
• W2892904655 created "2018-10-05" @default.
• W2892904655 creator A5011683384 @default.
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• W2892904655 date "2020-10-01" @default.
• W2892904655 modified "2023-09-26" @default.
• W2892904655 title "SurfelMeshing: Online Surfel-Based Mesh Reconstruction" @default.
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• W2892904655 doi "https://doi.org/10.1109/tpami.2019.2947048" @default.
• W2892904655 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31613751" @default.
• W2892904655 hasPublicationYear "2020" @default.
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