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GAIL: Geometry-aware Automatic Image Localization

By Luca Benedetti, Massimiliano Corsini, Matteo Dellepiane, Paolo Cignoni and Roberto Scopigno


The access and integration of the massive amount of information, that can be provided by the web, can be of great help in a number of fields, including tourism and advertising of artistic sites. A “virtual visit ” of a place can be a valuable experience before, during and after the experience on-site. For this reason, the contribution from the public could be merged to provide a realistic and immersive visit of known places. We propose an automatic image localization system, which is able to recognize the site that has been framed, and calibrate it on a pre-existing 3D representation. The system is characterized by very high accuracy and it is able to validate, in a completely unsupervised manner, the result of the localization. Given an unlocalized image, the system selects a relevant set of pre-localized images, performs a Structure from Motion partial reconstruction of this set and then obtain an accurate camera calibration of the image with respect to the model by minimizing distances between projections on the model surface of corresponding image features. The accuracy reached is enough to seamlessly view the input image correctly super-imposed in the 3D scene.

Year: 2013
OAI identifier: oai:CiteSeerX.psu:
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