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• W2167335287 abstract "Robust integration of range images is an important task for building high-quality 3D models. Since range images, and in particular range maps from stereo vision, may have a substantial amount of outliers, any integration approach aiming at high-quality models needs an increased level of robustness. Additionally, a certain level of regularization is required to obtain smooth surfaces. Computational efficiency and global convergence are further preferable properties. The contribution of this paper is a unified framework to solve all these issues. Our method is based on minimizing an energy functional consisting of a total variation (TV) regularization force and an L1 data fidelity term. We present a novel and efficient numerical scheme, which combines the duality principle for the TV term with a point-wise optimization step. We demonstrate the superior performance of our algorithm on the well-known Middlebury multi-view database and additionally on real-world multi-view images." @default.
• W2167335287 created "2016-06-24" @default.
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• W2167335287 date "2007-01-01" @default.
• W2167335287 modified "2023-10-01" @default.
• W2167335287 title "A Globally Optimal Algorithm for Robust TV-L¹ Range Image Integration" @default.
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• W2167335287 doi "https://doi.org/10.1109/iccv.2007.4408983" @default.
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