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Contenuto archiviato il 2024-06-18

Visual Recognition

Obiettivo

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.

Invito a presentare proposte

ERC-2008-AdG
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Meccanismo di finanziamento

ERC-AG - ERC Advanced Grant

Istituzione ospitante

THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Contributo UE
€ 1 872 056,00
Indirizzo
WELLINGTON SQUARE UNIVERSITY OFFICES
OX1 2JD Oxford
Regno Unito

Mostra sulla mappa

Regione
South East (England) Berkshire, Buckinghamshire and Oxfordshire Oxfordshire
Tipo di attività
Higher or Secondary Education Establishments
Ricercatore principale
Andrew Zisserman (Prof.)
Contatto amministrativo
Gill Wells (Ms.)
Collegamenti
Costo totale
Nessun dato

Beneficiari (1)