| dc.description.abstract | In the last decades we have assisted to a growing need for security in many public environments. According
to a study recently conducted by the European Security Observatory, one half of the entire population is
worried about the crime and requires the law enforcement to be protected.
This consideration has lead the proliferation of cameras and microphones, which represent a suitable solution
for their relative low cost of maintenance, the possibility of installing them virtually everywhere and, finally,
the capability of analysing more complex events. However, the main limitation of this traditional audiovideo
surveillance systems lies in the so called psychological overcharge issue of the human operators
responsible for security, that causes a decrease in their capabilities to analyse raw data flows from multiple
sources of multimedia information; indeed, as stated by a study conducted by Security Solutions magazine,
after 12 minutes of continuous video monitoring, a guard will often miss up to 45% of screen activity. After
22 minutes of video, up to 95% is overlooked.
For the above mentioned reasons, it would be really useful to have available an intelligent surveillance
system, able to provide images and video with a semantic interpretation, for trying to bridge the gap between
their low-level representation in terms of pixels, and the high-level, natural language description that a
human would give about them.
On the other hand, this kind of systems, able to automatically understand the events occurring in a scene,
would be really useful in other application fields, mainly oriented to marketing purposes. Especially in the
last years, a lot of business intelligent applications have been installed for assisting decision makers and for giving an organization’s employees, partners and suppliers easy access to the information they need to
effectively do their jobs... [edited by author] | en_US |
