The Placing Task is a yearly challenge offered by the MediaEval Multimedia Benchmarking
Initiative that requires participants to develop algorithms that automatically predict the geo …

The “crowd” has become a very important geospatial data provider. Specifically, nonexpert
users have been providing a wealth of quantitative geospatial data (eg, geotagged tweets or …

Indoor positioning allows for many commercially viable applications, such as navigation,
behavior and movement tracking, and augmented reality (AR). These applications all …

The sixth edition of the Placing Task at MediaEval introduces two new sub-tasks:(1) locale-
based placing, which emphasizes the need to move away from an evaluation purely based …

We present a method for profiling businesses at specific locations that is based on mining
information from social media. The method matches geo-tagged tweets from Twitter against …

Nowadays, people tend to share their personal photos, taken while they are traveling, to the
social media sharing websites, such as Flickr. There is also convenient access to the large …

In this paper we propose methods to extract geographically relevant information in a
multimedia recording using its audio. Our method primarily is based on the fact that urban …

One of the desiderata in machine intelligence is that machines must be able to comprehend
sounds as humans do. They must know about various sounds, associate them with physical …

This paper describes Imcube's geo-referencing approach, experiments, and results at the
MediaEval 2015 Placing Task benchmark. This task requires to develop techniques to …

In this paper, we study the problem of urban image geo-localization, where the aim is to
estimate the real-world location in which an image was taken. Among the previous …