The recent technological advancement of computing systems allows today to find computers with extremely advanced numerical processing capabilities. In particular, the use of Graphics Processing Units (GPUs) for image and multimedia content processing and classification is experiencing a phase of intense development thanks to the deep-seated scientific research conducted in recent years (Deep Learning). Deep Learning is a branch of Machine Learning that uses complex neural networks for a variety of applications. Among these, the application area of  automatic classification of audiovisual content is certainly one of the most interesting from the strategic point of view for RAI.

Visual search technology allows users to search and match image and video contents depicting the same objects, such as buildings, paintings and logos, based on visual similarities and without the need of querying for manually generated metadata.

RAI CRIT is supporting research to extend cloud object store technologies to address emerging media industry requirements, such as scalability, efficiency and adaptability of production and archiving workflows.

This project deals with the design and implementation of architecture and systems for companion screen applications.

The advent of RDF (Resource Description Framework) technology in the first half of the 2000’s, followed by RDF Schema and OWL (Web Ontology Language), represented a quantum leap in the possibility of concretely using semantic networks in the most varied applications. In the field of multimedia applications, among which we can include television production and archiving in general, they are by now an indispensable ingredient for semantic enriching and contextualisation  of content for a very wide range of purposes (from automatic documentation to content recommendations systems). This project aims at exploring in detail these possibilities by defining and implementing prototypical content semantic enrichment systems exploiting existing Knowledge Base and possibly extending/creating new domain ontologies.