http://www.cnr.it/ontology/cnr/individuo/prodotto/ID294048
Fast and simple automatic alignment of large sets of range maps (Articolo in rivista)
- Type
- Label
- Fast and simple automatic alignment of large sets of range maps (Articolo in rivista) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.cag.2014.12.002 (literal)
- Alternative label
Pingi P., Corsini M., Ganovelli F., Scopigno R. (2014)
Fast and simple automatic alignment of large sets of range maps
in Computers & graphics
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Pingi P., Corsini M., Ganovelli F., Scopigno R. (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
- Grant agreement: 323567
Tipo Progetto: EU_FP7 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.sciencedirect.com/science/article/pii/S0097849314001447 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Note
- PuMa (literal)
- Scopu (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy. (literal)
- Titolo
- Fast and simple automatic alignment of large sets of range maps (literal)
- Abstract
- We present a very fast and simple-to-implement algorithm for the automatic registration of a large number of range maps. The proposed algorithm exploits a compact and GPU-friendly descriptor specifically designed for the alignment of this type of data. This pairwise registration algorithm, which also includes a simple mechanism to avoid to get false positives, is part of a system capable to align a sequence of up to hundreds of range maps in few minutes. In order to reduce the number of pairs to align in the case of unordered range maps we use a prioritization strategy based on the fast computation of the correlation between range maps through FFT. The proposed system does not need any user input and it was tested successfully on a large variety of datasets coming from real acquisition campaigns. (literal)
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