Objective The goal of computer vision is to interpret complex visual scenes, by recognizing objects and understanding their spatial arrangement within the scene. Achieving this involves learningcategories from annotated training images. In the current paradigm, each category is learned starting from scratch without any previous knowledge. This is in contrast with how humans learn, who accumulate knowledge about visual concepts which they reuse to help learning new concepts.The goal of this project is to develop a new paradigm where computers learn visual concepts on top of what they already know, as opposed to learning every concept from scratch. We propose to progressively learn a vast body of visual knowledge, coined Visual Culture, from a variety of available datasets. We will acquire models of the appearance and shape of categories in general, models of specific categories, and models of their spatial organization into scenes. We will start learning from datasets with high degree of supervision and then gradually move to datasets with lower degrees. At each stage we will employ the current body of knowledge to support learning with less supervision. After acquiring Visual Culture from existing datasets, the machine will be ready to learn further with little or no supervision, for example from the Internet. Visual Culture is related to ideas in other fields, but no similar endeavor was undertaken in Computer Vision yet.This project will make an important step toward mastering the complexity of the visual world, by advancing the state-of-the-art in terms of the number of categories that can be localized, and inthe variability covered by each model. Moreover, Visual Culture is more than a mere collection of isolated categories, it is is a web of object, background, and scene models connected by spatial relations and sharing visual properties. This will bring us closer to image understanding, the automatic interpretation of complex novel images. Fields of science natural sciencescomputer and information sciencesinternetnatural sciencescomputer and information sciencesartificial intelligencecomputer vision Programme(s) 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) Topic(s) ERC-SG-PE6 - ERC Starting Grant - Computer science and informatics Call for proposal ERC-2012-StG_20111012 See other projects for this call Funding Scheme ERC-SG - ERC Starting Grant Coordinator THE UNIVERSITY OF EDINBURGH Address Old college, south bridge EH8 9YL Edinburgh United Kingdom See on map Region Scotland Eastern Scotland Edinburgh Activity type Higher or Secondary Education Establishments Principal investigator Vittorio Ferrari (Dr.) Administrative Contact Alan Kennedy (Mr.) Links Contact the organisation Opens in new window Website Opens in new window EU contribution No data Beneficiaries (1) Sort alphabetically Sort by EU Contribution Expand all Collapse all THE UNIVERSITY OF EDINBURGH United Kingdom EU contribution € 1 481 516,00 Address Old college, south bridge EH8 9YL Edinburgh See on map Region Scotland Eastern Scotland Edinburgh Activity type Higher or Secondary Education Establishments Principal investigator Vittorio Ferrari (Dr.) Administrative Contact Alan Kennedy (Mr.) Links Contact the organisation Opens in new window Website Opens in new window Other funding No data
