Vidi Video: Interactive semantic video search with a large theasurus of machine-learned audio-visual concepts

Video is vital to society and economy. It plays a key role in the news, cultural heritage documentaries and surveillance, and it will soon be the natural form of communication for the Internet and mobile phones. Digital video will bring more formats and opportunities and it is certain the the consumer and the professional need advanced storage and search technology for the management of large-scale video assets. This project takes on the challenge of creating a substantially enhanced semantic access to video, implemented in a search engine.

 

Vidi Video will boost the performance of video search by forming a 1000 element of thesaurus detecting instances of audio, visual or mixed-media content. The consortium presents excellent expertise and resource: the machine learning with active 1-class classifiers to minimize the need for annotated examples is lead by the University of Surrey, UK. Video stream processing is lead by Centre For Research and Techonolgy Hellas, Greece. Another component is audio event detection, lead by INESC-ID, Portugal. Visual image processing is lead by the University of Amsterdam, the Netherlands. The university of Florence, Italy, leads the efforts in interaction, and Centro de Vision por Computador, spain leads software consolidation. Finally, Bleeld & Geluid, the Netherlands, and Fondazione Rinascimento Digitale, Italy, as application stakeholders, prove data and perform evaluation and dissemination.