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Great EU-funded Innovations

Innovation

New methods for people and music identification for more accurate video segmentation

Market Maturity

Exploring: These are innovations that are actively exploring value creation opportunities.More about market maturity categories

Innovation topic

Education, Content & Creativity

Date of analysis

Innovation Radar's analysis of this innovation is based on data collected on 30/08/2019

Go to market needs

Needs that, if addressed, can increase the chances this innovation gets to (or closer to) the market incude:

  • Secure capital
  • Project

    This innovation was developed under the Horizon 2020 project MeMAD. Details of this project are provided below:

    Project acronym: MeMAD

    Project Title: Methods for Managing Audiovisual Data: Combining Automatic Efficiency with Human Accuracy

    Project description: Audiovisual media content created and used in films and videos is key for people to communicate and entertain. It has also become an essential resource of modern history, since a large portion of memories and records of the 20th and 21st centuries are audiovisual. To fully benefit from this asset, fast and effective methods are needed to cope with the rapidly growing audiovisual big data that are collected in digital repositories and used internationally. MeMAD will provide novel methods for an efficient re-use and re-purpose of multilingual audiovisual content which revolutionize video management and digital storytelling in broadcasting and media production. We go 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. While current methods work mainly for English, MeMAD will handle multilingual source material and produce multilingual descriptions and thus enhance the user experience. Our method interactively integrates the latest research achievements in deep neural network techniques in computer vision with knowledge bases, human and machine translation in a continuously improving machine learning framework. This results in detailed, rich descriptions of the moving images, speech, and audio, which enable people working in the Creative Industries to access and use audiovisual information in more effective ways. Moreover,the intermodal translation from images and sounds into words will attract millions of new users to audiovisual media, including the visually and hearing impaired. Anyone using audiovisual content will also benefit from these verbalisations as they are non-invasive surrogates for visual and auditory information, which can be processed without the need of actually watching or listening, matching the new usage of video consumption on mobile devices.

    Project end date: 31/12/2020

    More info:

    • Read more about this project on CORDIS (find names of contact persons and their phone numbers on the CORDIS page)

    • Details of this project on the Horizon 2020 dashboard

    Key Innovator(s)

    INSTITUT NATIONAL DE L'AUDIOVISUEL

    BRY-SUR-MARNE, FR

    Public body

    UNIVERSITY OF SURREY

    GUILDFORD, UK

    Higher Education Institute / Research Centre