Tweet Geolocation Error Estimation

Exploiting Contextual Information for Fine-Grained Tweet Geolocation

Kernel Density Estimation for Text-Based Geolocation

Text-based geolocation classifiers often operate with a grid-based view of the world. Predicting document location of origin based on text content on a geodesic grid is computationally attractive since many standard methods for supervised document classification carry over unchanged to geolocation in the form of predicting a most probable grid cell for a document. However, the grid-based approa...

Optimizing Content-Based Image Retrieval for Geolocation Estimation

The prediction of geo-graphical location at which an image is taken is drawing increasing attention in recent research. However, one major limitation of most current research is that it focuses mostly on improving the geolocation prediction performance while ignoring the problem of index size, which is helpful in saving storage space. Traditional image retrieval index reduction approach can be ...

Pose Estimation Using Both Points and Lines for Geolocation

This paper identifies and fills the probably last two missing items in minimal pose estimation algorithms using points and lines. Pose estimation refers to the problem of recovering the pose of a calibrated camera given known features (points or lines) in the world and their projections on the image. There are four minimal configurations using point and line features: 3 points, 2 points and 1 l...

Leveraging Buffering Delay Estimation for Geolocation of Internet Hosts

Geolocation techniques aim at determining the geographic location of an Internet host based on its IP address. Currently, measurement-based geolocation techniques disregard the buffering delays that may be introduced at each hop along the path taken by probe packets. To fill this gap, we propose the GeoBuD (Geolocation using Buffering Delay estimation) approach. Although the network delay and t...