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EnglishThis paper casts the global registration of multiple 3D point-sets into a low-rank and sparse decomposition problem. This neat mathematical formulation caters for missing data, outliers and noise, and it benefits from a wealth of available decomposition algorithms that can be plugged-in. Experimental results show that this approach compares favourably to the state of the art in terms of precision and speed, and it outperforms all the analysed techniques as for robustness to outliers
Global registration of 3D point sets via LRS decomposition / Arrigoni, Federica; Rossi, Beatrice; Fusiello, Andrea. - 9908(2016), pp. 489-504. ((Intervento presentato al convegno 14th European Conference on Computer Vision (ECCV) tenutosi a Amsterdam nel OCT 08-16, 2016.
| Titolo: | Global registration of 3D point sets via LRS decomposition |
| Autori: | |
| Data di pubblicazione: | 2016 |
| Serie: | |
| Citazione: | Global registration of 3D point sets via LRS decomposition / Arrigoni, Federica; Rossi, Beatrice; Fusiello, Andrea. - 9908(2016), pp. 489-504. ((Intervento presentato al convegno 14th European Conference on Computer Vision (ECCV) tenutosi a Amsterdam nel OCT 08-16, 2016. |
| Abstract: | This paper casts the global registration of multiple 3D point-sets into a low-rank and sparse decomposition problem. This neat mathematical formulation caters for missing data, outliers and noise, and it benefits from a wealth of available decomposition algorithms that can be plugged-in. Experimental results show that this approach compares favourably to the state of the art in terms of precision and speed, and it outperforms all the analysed techniques as for robustness to outliers |
| Handle: | http://hdl.handle.net/11390/1097670 |
| ISBN: | 9783319464923 |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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