Objective "My goal in the project is to develop and analyze algorithms that use continuous, open-ended machine learning from visual input data (images and videos) in order to interpret visual scenes on a level comparable to humans.L3ViSU is based on the hypothesis that we can only significantly improve the state of the art in computer vision algorithms by giving them access to background and contextual knowledge about the visual world, and that the most feasible way to obtain such knowledge is by extracting it (semi-) automatically from incoming visual stimuli. Consequently, at the core of L3ViSU lies the idea of life-long visual learning.Sufficient data for such an effort is readily available, e.g. through digital TV-channels and media-sharing Internet platforms, but the question of how to use these resources for building better computer vision systems is wide open. In L3ViSU we will rely on modern machine learning concepts, representing task-independent prior knowledge as prior distributions and function regularizers. This functional form allows them to help solving specific tasks by guiding the solution to ""reasonable"" ones, and to suppress mistakes that violate ""common sense"". The result will not only be improved prediction quality, but also a reduction in the amount of manual supervision necessary, and the possibility to introduce more semantics into computer vision, which has recently been identified as one of the major tasks for the next decade.L3ViSU is a project on the interface between computer vision and machine learning. Solving it requires expertise in both areas, as it is represented in my research group at IST Austria. The life-long learning concepts developed within L3ViSU, however, will have impact outside of both areas, let it be as basis of life-long learning system with a different focus, such as in bioinformatics, or as a foundation for projects of commercial value, such as more intelligent driver assistance or video surveillance systems." Fields of science natural sciencescomputer and information sciencesinternetnatural sciencescomputer and information sciencesartificial intelligencecomputer visionnatural sciencescomputer and information sciencesartificial intelligencemachine learning 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 Host institution INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA EU contribution € 1 464 711,68 Address Am Campus 1 3400 Klosterneuburg Austria See on map Region Ostösterreich Niederösterreich Wiener Umland/Nordteil Activity type Higher or Secondary Education Establishments Principal investigator Christoph Lampert (Dr.) Administrative Contact Carla Mazuheli-Chibidziura (Mrs.) Links Contact the organisation Opens in new window Website Opens in new window Total cost No data Beneficiaries (1) Sort alphabetically Sort by EU Contribution Expand all Collapse all INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA Austria EU contribution € 1 464 711,68 Address Am Campus 1 3400 Klosterneuburg See on map Region Ostösterreich Niederösterreich Wiener Umland/Nordteil Activity type Higher or Secondary Education Establishments Principal investigator Christoph Lampert (Dr.) Administrative Contact Carla Mazuheli-Chibidziura (Mrs.) Links Contact the organisation Opens in new window Website Opens in new window Total cost No data
