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.
GAIL: Geometry-aware Automatic Image Localization / Benedetti, Luca; Corsini, M; Dellepiane, Matteo; Cignoni, Paolo; Scopigno, Roberto. - 2:(2013), pp. 31-40. (Intervento presentato al convegno 8th International Conference on Computer Vision Theory and Applications, VISAPP 2013 tenutosi a Barcelona, esp nel 21-24 February 2013).
GAIL: Geometry-aware Automatic Image Localization
Corsini M;
2013
Abstract
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.
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