Localizing Unordered Panoramic Images Using the Levenshtein Distance

This paper proposes a feature-based method for recovering 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 regarding 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 reconstruction with the aid of bundle adjustment, distributes the reconstruction errors among images. The method is demonstrated on several unordered sets of panoramic images obtained in an in...

• Type: Conference
• Year: 2007
• Where: ICCV
• Authors: Damien Michel, Antonis A. Argyros, Manolis I. A. Lourakis
• Keywords: Computer Vision, ICCV 2007, Imaged Environment, Levenshtein Distance, Panoramic Images, Priori Order Information, Underlying Environment Points