Higher Order Visual Search for Information in Multidimensional Data Sets


Professor Dr.-Ing. Marcus Andreas Magnor, Braunschweig
Technische Universität Carolo-Wilhelmina zu Braunschweig
Institut für Computergraphik

Professor Dr. Holger Theisel, Magdeburg
Otto-von-Guericke-Universität Magdeburg
Institut für Simulation und Graphik


Higher Order Visual Search for Information in Multidimensional Data Sets (Publications)


The project extends the results of the exhaustive visual search approach (DFG MA2555/6-1 and DFG TH692/6-1) to address higher-order relations in multidimensional data sets which are to be searched, modeled, and analyzed by applying image analysis techniques to a large number of automatically created visualizations. Here, "higher-order relations" refers to considering non-trivial relations between two dimensions described by user-drawn sketches, relations between more than two dimensions, and relations only present in continuous (nondiscrete) data sets. For all three cases, solutions based on the exhaustive visual search shall be explored. Methodically, the approaches are based on finding new quality measures for different visualizations, analyzing 3D visualizations, and searching features in continuous visualizations. While focusing on developing general (applicationindependent) principles, our methods will be tested on high-dimensional and large data sets provided by our cooperation partners from climate research and medical imaging.