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Contenido archivado el 2024-06-18

Visual Recognition

Objetivo

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.

Convocatoria de propuestas

ERC-2008-AdG
Consulte otros proyectos de esta convocatoria

Régimen de financiación

ERC-AG - ERC Advanced Grant

Institución de acogida

THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Aportación de la UE
€ 1 872 056,00
Dirección
WELLINGTON SQUARE UNIVERSITY OFFICES
OX1 2JD Oxford
Reino Unido

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Región
South East (England) Berkshire, Buckinghamshire and Oxfordshire Oxfordshire
Tipo de actividad
Higher or Secondary Education Establishments
Investigador principal
Andrew Zisserman (Prof.)
Contacto administrativo
Gill Wells (Ms.)
Enlaces
Coste total
Sin datos

Beneficiarios (1)