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Visual Recognition

Objective

Our goal is to develop the fundamental knowledge to design a visual system that is able to learn, recognize and retrieve quickly and accurately thousands of visual categories, including materials, objects, scenes, human actions and activities. A ``visual google'' for images and videos -- able to search for the ``nouns'' (objects, scenes), ``verbs'' (actions/activities) and adjectives (materials, patterns) of visual content. The time is right for making great progress in automated visual recognition: imaging geometry is well understood, image features are now highly developed, and relevant statistical models and machine learning algorithms are well-advanced. Our goal is to make a quantum leap in the capabilities of visual recognition in real-life scenarios. The outcomes of this research will impact any applications where visual recognition is useful, and will enable new applications entirely: effortlessly searching and annotating home image and video collections on their visual content; searching and annotating large commercial image and video archives (e.g. YouTube); surveillance; using an image, rather than text, to access the web and hence identify its visual content.

Field of science

  • /humanities/arts/modern and contemporary art/film
  • /natural sciences/mathematics/applied mathematics/statistics and probability

Call for proposal

ERC-2008-AdG
See other projects for this call

Funding Scheme

ERC-AG - ERC Advanced Grant

Host institution

THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Address
Wellington Square University Offices
OX1 2JD Oxford
United Kingdom
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 1 872 056
Principal investigator
Andrew Zisserman (Prof.)
Administrative Contact
Gill Wells (Ms.)

Beneficiaries (1)

THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
United Kingdom
EU contribution
€ 1 872 056
Address
Wellington Square University Offices
OX1 2JD Oxford
Activity type
Higher or Secondary Education Establishments
Principal investigator
Andrew Zisserman (Prof.)
Administrative Contact
Gill Wells (Ms.)