This paper deals with the synchronization problem, which arises in multiple 3D point-set registration and in structure-from-motion. The problem is formulated as a low-rank and sparse matrix decom- position that caters for missing data, outliers and noise, and it benefits from a wealth of available decomposition algorithms that can be plugged-in. A minimization strategy, dubbed R-GoDec, is also proposed. Experimental results on simulated and real data show that this approach offers a good trade-off between resistance to outliers and speed.

Robust synchronization in SO(3) and SE(3) via low-rank and sparse matrix decomposition / Arrigoni, Federica; Rossi, Beatrice; Fragneto, Pasqualina; Fusiello, Andrea. - In: COMPUTER VISION AND IMAGE UNDERSTANDING. - ISSN 1077-3142. - 174:(2018), pp. 95-113. [10.1016/j.cviu.2018.08.001]

Robust synchronization in SO(3) and SE(3) via low-rank and sparse matrix decomposition

Arrigoni, Federica;
2018-01-01

Abstract

This paper deals with the synchronization problem, which arises in multiple 3D point-set registration and in structure-from-motion. The problem is formulated as a low-rank and sparse matrix decom- position that caters for missing data, outliers and noise, and it benefits from a wealth of available decomposition algorithms that can be plugged-in. A minimization strategy, dubbed R-GoDec, is also proposed. Experimental results on simulated and real data show that this approach offers a good trade-off between resistance to outliers and speed.
2018
Arrigoni, Federica; Rossi, Beatrice; Fragneto, Pasqualina; Fusiello, Andrea
Robust synchronization in SO(3) and SE(3) via low-rank and sparse matrix decomposition / Arrigoni, Federica; Rossi, Beatrice; Fragneto, Pasqualina; Fusiello, Andrea. - In: COMPUTER VISION AND IMAGE UNDERSTANDING. - ISSN 1077-3142. - 174:(2018), pp. 95-113. [10.1016/j.cviu.2018.08.001]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/272072
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