Objective One of the most fundamental challenges in computer vision is to reliably establish correspondence - how to match a location in one image to its counterpart in another. It lies at the heart of numerous important problems, for example stereo, optical flow, tracking and the reconstruction of scene geometry from several photographs. The most popular approaches to solve these problems are based on the simplification that a scene point looks the same from wherever and whenever it is observed. However, this is fundamentally wrong, since its color changes with viewing direction and illumination. This invariably leads to failures when dealing with reflecting or transparent surfaces or changes in lighting, which commonly occur in natural scenes.We therefore propose to radically rethink the underlying assumptions and work with light fields to describe the visual appearance of a scene. Compared to a traditional image, a light field offers information not only about the amount of incident light, but also the direction where it is coming from. In effect, the light field implicitly captures scene geometry and reflectance properties. In the following, we will argue that variational algorithms based on light field data have the potential to considerably advance the state-of-the-art in all image analysis applications related to lighting-invariant robust matching, geometry reconstruction or reflectance estimation.Since computational cameras are currently making rapid progress, we believe that light fields will soon become a focus of computer vision research. Already, commercial plenoptic cameras allow to easily capture the light field of a scene and are suitable for real-world applications, while a recent survey even predicted that in about 20 years time, every consumer camera will be a light field camera. Our research will investigate fundamental mathematical tools and algorithms which will substantially contribute to drive this development. Fields of science engineering and technologymaterials engineeringcolorsengineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensorsnatural sciencescomputer and information sciencesartificial intelligencecomputer visionnatural sciencesmathematicspure mathematicsgeometry 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-2013-StG See other projects for this call Funding Scheme ERC-SG - ERC Starting Grant Host institution UNIVERSITAT KONSTANZ EU contribution € 1 466 100,00 Address UNIVERSITATSSTRASSE 10 78464 Konstanz Germany See on map Region Baden-Württemberg Freiburg Konstanz Activity type Higher or Secondary Education Establishments Principal investigator Bastian Goldlücke (Dr.) Administrative Contact Christina Leib (Ms.) Links Contact the organisation Opens in new window Website Opens in new window Total cost No data Beneficiaries (2) Sort alphabetically Sort by EU Contribution Expand all Collapse all UNIVERSITAT KONSTANZ Germany EU contribution € 1 466 100,00 Address UNIVERSITATSSTRASSE 10 78464 Konstanz See on map Region Baden-Württemberg Freiburg Konstanz Activity type Higher or Secondary Education Establishments Principal investigator Bastian Goldlücke (Dr.) Administrative Contact Christina Leib (Ms.) Links Contact the organisation Opens in new window Website Opens in new window Total cost No data RUPRECHT-KARLS-UNIVERSITAET HEIDELBERG Participation ended Germany EU contribution No data Address SEMINARSTRASSE 2 69117 Heidelberg See on map Region Baden-Württemberg Karlsruhe Heidelberg, Stadtkreis Activity type Higher or Secondary Education Establishments Administrative Contact Norbert Huber (Dr.) Links Contact the organisation Opens in new window Website Opens in new window Total cost No data