The project goes far beyond the state-of-the-art automatic video description methods by making the machine learn from the human. The resulting description is thus not only a time-aligned semantic extraction of objects but makes use of the audio and recognizes action sequences.
MeMAD addresses the challenge of improving the discoverability of audiovisual data, by developing novel methods for accessing and using the content. As a bonus, the methods developed for this automatic analysis, have a tremendous effect on the costs of the multimedia production processes: tasks that earlier have required hundreds of hours of human labour can be carried out with just hours of machine work.
Also, the project makes audiovisual content smarter and more appealing to users by interpreting the content and by providing supporting links to other media assets and external information sources. The media description and linking techniques developed by MeMAD use new and emerging technologies, such as deep and recurrent neural networks, machine learning, artificial intelligence and big data analysis. In other words, technologies capable of learning from humans, to make media smarter and more accessible for everybody.
- From 2018-01-01 to 2020-12-31
- Total cost: EUR 3 431 593,75
- EU contribution: EUR 3 431 593,75
- Topic: ICT-20-2017 - Tools for smart digital content in the creative industries
- Call for proposal: H2020-ICT-2017-1
- Funding scheme: RIA - Research and Innovation action