Prof. Bernt Schiele
Multimodal Interactive Systems
Department of Computer Science
TU Darmstadt
Germany
schiele@informatik.tu-darmstadt.de
We describe various approaches capable of simultaneous recognition and localization of multiple object classes using a combination of generative and discriminative methods. A first approach uses a novel hierarchical representation allows to represent individual images as well as various objects classes in a single similarity invariant model. The recognition method is based on a codebook representation where appearance clusters built from edge based features are shared among several object classes. A probabilistic model allows for reliable detection of various objects in the same image. A second approach uses a dense representation and a topic distribution model to obtain an intermediate and general representation that is shared across object categories. Combined with discriminative methods these systems show excellent performance on several object categories.
Bernt Schiele is Full Professor of Computer Science at Darmsadt University of Technology since April 2004.
He studied computer science at the University of Karlsruhe, Germany. He worked on his master thesis in the field of robotics in Grenoble, France, where he also obtained the "diplome d'etudes approfondies d'informatique". In 1994 he worked in the field of multi-modal human-computer interfaces at Carnegie Mellon University, Pittsburgh, PA, USA in the group of Alex Waibel. In 1997 he obtained his PhD from INP Grenoble, France under the supervision of Prof. James L. Crowley in the field of computer vision. The title of his thesis was "Object Recognition using Multidimensional Receptive Field Histograms". Between 1997 and 2000 he was postdoctoral associate and Visiting Assistant Professor with the group of Prof. Alex Pentland at the Media Laboratory of the Massachusetts Institute of Technology, Cambridge, MA, USA. From 1999 until 2004 he was Assistant Professor at the Swiss Federal Institute of Technoly in Zurich (ETH Zurich).
His main research interests are in computer vision, perceptual computing, robotics, statistical learning methods, wearable computers, and integration of multi-modal sensor data. He is particularly interested in developing methods which work under real-world conditions.