Computer
Consistent Line Clusters for Building Recognition in CBIR
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Real-Time Mobility Tracking Algorithms for Cellular Networks Based on Kalman Filtering
IEEE Transactions on Mobile Computing
Sharing the square: collaborative leisure in the city streets
ECSCW'05 Proceedings of the ninth conference on European Conference on Computer Supported Cooperative Work
Enabling Mobile Phones To Support Large-Scale Museum Guidance
IEEE MultiMedia
Location Estimation via Support Vector Regression
IEEE Transactions on Mobile Computing
The MPEG-7 Multimedia Database System (MPEG-7 MMDB)
Journal of Systems and Software
On the hybrid aid-localization for outdoor augmented reality applications
Proceedings of the 2008 ACM symposium on Virtual reality software and technology
Position Location Techniques and Applications
Position Location Techniques and Applications
A hybrid SS-ToA wireless NLoS geolocation based on path attenuation: mobile position estimation
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Mobility Tracking in Cellular Networks Using Particle Filtering
IEEE Transactions on Wireless Communications
The MPEG-7 visual standard for content description-an overview
IEEE Transactions on Circuits and Systems for Video Technology
Sense-And-Trace: a privacy preserving distributed geolocation tracking system
SP'12 Proceedings of the 20th international conference on Security Protocols
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Modern mobile devices integrating sensors, like accelerometers and cameras, are paving the way to the definition of high-quality and accurate geolocation solutions based on the informations acquired by these sensors, and data collected and managed by GSM/3G networks. In this paper, we present a technique that provides geolocation and mobility prediction of mobile devices, mixing the location information acquired with the GSM/3G infrastructure and the results of a landmark matching achieved thanks to the camera integrated on the mobile devices. Our geolocation approach is based on an advanced Time-Forwarding algorithm and on database correlation technique over Received Signal Strength Indication (RSSI) data, and integrates information produced by a landmark recognition infrastructure, to enhance algorithm performances in those areas with poor signal and low accurate geolocation. Performances of the algorithm are evaluated on real data from a complex urban environment.