An Efficient Preconditioner and a Modified RANSAC for Fast and Robust Feature Matching (Contributo in atti di convegno)

Type
Label
  • An Efficient Preconditioner and a Modified RANSAC for Fast and Robust Feature Matching (Contributo in atti di convegno) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Alternative label
  • Anders Hast, Andrea Marchetti (2012)
    An Efficient Preconditioner and a Modified RANSAC for Fast and Robust Feature Matching
    in International Conferences in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG'12), Plzen
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Anders Hast, Andrea Marchetti (literal)
Pagina inizio
  • 1 (literal)
Pagina fine
  • 8 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • cnr.iit/2012-A2-007 (literal)
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Uppsala University, Sweden; CNR-IIT, Pisa, Italy (literal)
Titolo
  • An Efficient Preconditioner and a Modified RANSAC for Fast and Robust Feature Matching (literal)
Abstract
  • Standard RANSAC does not perform very well for contaminated sets, when there is a majority of outliers. We present a methodthat overcomes this problem by transforming the problem into a 2D position vector space, where an ordinary cluster algorithmcan be used to find a set of putative inliers. This set can then easily be handled by a modified version of RANSAC that drawssamples from this set only and scores using the entire set. This approach works well for moderate differences in scale androtation. For contaminated sets the increase in performance is in several orders of magnitude. We present results from testingthe algorithm using the Direct Linear Transformation on aerial images and photographs used for panographs (literal)
Prodotto di
Autore CNR
Insieme di parole chiave

Incoming links:


Prodotto
Autore CNR di
Insieme di parole chiave di
data.CNR.it