Objective
A massive and ever growing amount of digital image and video content
is available today, on sites such as
Flickr and YouTube, in audiovisual archives such as those of BBC and
INA, and in personal collections. In most cases, it comes with
additional information, such as text, audio or other metadata, that forms a
rather sparse and noisy, yet rich and diverse source of annotation,
ideally suited to emerging weakly supervised and active machine
learning technology. The ALLEGRO project will take visual recognition
to the next level by using this largely untapped source of data to
automatically learn visual models. The main research objective of
our project is the development of new algorithms and computer software
capable of autonomously exploring evolving data collections, selecting
the relevant information, and determining the visual models most
appropriate for different object, scene, and activity categories. An
emphasis will be put on learning visual models from video, a
particularly rich source of information, and on the representation of
human activities, one of today's most challenging problems in computer
vision. Although this project addresses fundamental research
issues, it is expected to result in significant advances in
high-impact applications that range from visual mining of the Web and
automated annotation and organization of family photo and video albums
to large-scale information retrieval in television archives.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- social sciences media and communications graphic design
- natural sciences computer and information sciences software
- natural sciences computer and information sciences artificial intelligence computer vision
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
ERC-2012-ADG_20120216
See other projects for this call
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Host institution
78153 Le Chesnay Cedex
France
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.