Coordinatore | THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie. |
Nazionalità Coordinatore | United Kingdom [UK] |
Totale costo | 1˙872˙056 € |
EC contributo | 1˙872˙056 € |
Programma | FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
Code Call | ERC-2008-AdG |
Funding Scheme | ERC-AG |
Anno di inizio | 2009 |
Periodo (anno-mese-giorno) | 2009-01-01 - 2014-12-31 |
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1 |
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Organization address
address: University Offices, Wellington Square contact info |
UK (OXFORD) | hostInstitution | 1˙872˙056.00 |
2 |
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Organization address
address: University Offices, Wellington Square contact info |
UK (OXFORD) | hostInstitution | 1˙872˙056.00 |
Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.
'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.'