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Our research focuses on image analysis to support precise alignment of geo-referenced information with the capturing camera view, where GPS and inertial measurements are used to support the registration with the visual environment.
The quality of AR Experience on mobile devices often depends on the precision with which the content is aligned with relevant features of the environment. A better experience is delivered when such information is locked onto the user's view rather than roughly overlayed from GPS and intertial sensor measurements. Visual registration is also a core functionality to enable geo-structured access to image databases such as flickr and panoramio, and opens up important new opportunities in environment monitoring from crowd-sourced media.
L. Porzi, S. Rota Bulo', E. Ricci: A Deeply-Supervised Deconvolutional Network for Horizon Line Detection, ACM on Multimedia Conference - ACMMM, Amsterdam, The Netherlands, October 2016
L. Porzi, S. Rota Bulo', O. Lanz, P. Valigi, E. Ricci: Learning Contours for Automatic Annotations of Mountains Pictures on a Smartphone. ACM/IEEE International Conference on Distributed Smart Cameras - ICSDC, Venezia, Italy, 4-7 November 2014
P. Chippendale, M. Zanin, M. Dalla Mura: Geo-positional Image Forensics through Scene-Terrain Registration. International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISAPP 2013, Barcelona, Spain, 21-24 February 2013
L. Porzi, E. Ricci, T. A. Ciarfuglia, M. Zanin: Visual-inertial Tracking on Android for Augmented Reality Applications. IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems - EESMS 2012 Perugia, Italy, September 28, 2012, pp. 35-41