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Localizing Unordered Panoramic Images Using the Levenshtein Distance Damien Michel, Antonis A. Argyros and Manolis I.A. Lourakis
 

Summary: Localizing Unordered Panoramic Images Using the Levenshtein Distance
Damien Michel, Antonis A. Argyros and Manolis I.A. Lourakis
Institute of Computer Science, Foundation for Research and Technology - Hellas
Vassilika Vouton, P.O. Box 1385, GR 711 10, Heraklion, Crete, GREECE
http://www.ics.forth.gr/cvrl
Abstract
This paper proposes a feature-based method for recov-
ering the relative positions of the viewpoints of a set of
panoramic images for which no a priori order information
is available, along with certain structure information re-
garding the imaged environment. The proposed approach
operates incrementally, employing the Levenshtein distance
to deduce the spatial proximity of image viewpoints and thus
determine the order in which images should be processed.
The Levenshtein distance also provides matches between
images, from which their underlying environment points can
be recovered. Recovered points that are visible in multiple
views permit the localization of more views which in turn
allow the recovery of more points. The process repeats until
all views have been localized. Periodic refinement of the re-

  

Source: Argyros, Antonis - Foundation of Research and Technology, Hellas & Department of Computer Science, University of Crete
Trahanias, Panos - Institute of Computer Science, Foundation of Research and Technology, Hellas

 

Collections: Computer Technologies and Information Sciences